Citation
Women and social stratification

Material Information

Title:
Women and social stratification the influence of mothers on women's social class
Creator:
Greenfield, Meredith
Place of Publication:
Denver, Colo.
Publisher:
University of Colorado Denver
Publication Date:
Language:
English
Physical Description:
xi, 131 leaves : ; 28 cm

Thesis/Dissertation Information

Degree:
Master's ( Master of Arts)
Degree Grantor:
University of Colorado Denver
Degree Divisions:
Department of Sociology, CU Denver
Degree Disciplines:
Sociology
Committee Chair:
Anderson, Richard Holmes
Committee Members:
Winterton, Jon A.
Flaming, Karl H.

Subjects

Subjects / Keywords:
Women -- Social conditions -- United States ( lcsh )
Social stratification -- United States ( lcsh )
Mothers and daughters -- United States ( lcsh )
Motherhood -- United States ( lcsh )
Motherhood ( fast )
Mothers and daughters ( fast )
Social stratification ( fast )
Women -- Social conditions ( fast )
United States ( fast )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Includes bibliographical references (leaves 124-131).
Thesis:
Sociology
General Note:
Department of Sociology
Statement of Responsibility:
by Meredith Greenfield.

Record Information

Source Institution:
|University of Colorado Denver
Holding Location:
|Auraria Library
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
50740733 ( OCLC )
ocm50740733
Classification:
LD1190.L66 2002m .G73 ( lcc )

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Full Text
WOMEN AND SOCIAL STRATIFICATION:
THE INFLUENCE OF MOTHERS ON
WOMEN'S SOCIAL CLASS
B. A., University of Colorado at Denver, 1999
A thesis submitted to the
University of Colorado at Denver
in partial fulfillment
of the requirements for the degree of
Master of Arts
Sociology
by
Meredith Greenfield
2002


This thesis for the Master of Arts Sociology
degree by
Meredith Greenfield
has been approved
by
ming


Greenfield, Meredith (M. A., Sociology)
Women and Social Stratification:
The Influence of Mothers on Women's Social Class
Thesis directed by Professor Richard Holmes Anderson
ABSTRACT
The continuing use of the conventional method for measuring social class,
using the family as the unit of measurement and only data on the male head-of-
household, fails to resolve the issue of the independent social position of women.
Women's growing autonomous social class identity is because of recent important
cultural and economic changes that affect their social stratification, such as
educational attainment, occupational prestige and changing demographics of the
family unit. Using intergenerational information from family of origin could
provide the indicators of social status needed as individual class position becomes
more independent of the family unit. This issue of intergenerational influences on
social class is explored by using data from the General Social Survey 1972
through 1998. The indicators used as independent variables are mothers' work
history, years of education, and occupational prestige. Women's work history,
years of education, occupational prestige, and subjective class identity are the
dependent variables. The results of this study show that after controlling for
fathers' and spouses' social class indictors, mothers' social class indicators are
significant predictors of the social class position of women.
This abstract represents the content of the candidate's thesis. I recommend
its publication.
Signed,
Richard'Holmes Anderson
Ul


ACKNOWLEDGEMENTS
Thank you to my advisor, Dr. Richard Holmes Anderson for his help and
patience. Thank you to the entire University of Colorado at Denver Department
of Sociology for providing an exciting and challenging Sociology program, that
encouraged me to persevere in my studies. Thank you to my husband, Julius
Wagner, for his unflagging support.


CONTENTS
Tables...................................................viii
CHAPTER
1. INTRODUCTION........................................... 1
2. LITERATURE REVIEW..................................... 10
A Brief Historical Overview........................ 10
Measuring Social Stratification.................... 13
Social Stratification Measurement and Women........ 17
Subjective Class Identification.................... 29
Social and Occupational Mobility of Women.......... 32
Socialization of Children.......................... 35
3. METHODOLOGY........................................... 40
Data............................................... 41
Sample........................................... 42
Variables and Indicators........................... 44
v


Method of Analysis..................................... 50
Limitations.......................................... 52
Data Limitations................................ 52
Other Limitations............................. 53
4. DATA ANALYSIS............................................. 56
Cross Tabulation Models for Comparing Women and
Their Mothers' Work History, Years of Education,
and Occupational Prestige.............................. 58
Separate Regression Models of Effects of Mothers,
Fathers', and Spouses' Years of Education and
Occupational Prestige on Women's Occupational Prestige
and Subjective Class Identity.......................... 68
Combined Regression Models of Effects of Mothers',
Fathers', and Spouses' Years of Education and
Occupational Prestige on Women's Occupational Prestige
and Subjective Class Identity.......................... 73
Combined Regression Models of Effects of Women's
Years of Education and Occupational Prestige and Mothers',
Fathers', and Spouses' Years of Education and Occupational
Prestige on Women's Subjective Class Identity.......... 78
Regression Models Effects of Women's Years of
Education and Occupational Prestige and Spouses'
Years of Education and Occupational Prestige on
Women's Subjective Class Identity...................... 83
Regression Models Comparing the Combined Effects
of Men's Years of Education and occupational Prestige
and the Years of Education and Occupational Prestige
of Mothers', Fathers', and Spouses' on Men's Subjective
Class Identity......................................... 87
vi


5. CONCLUSION................................. 95
APPENDIX
A. Chapter 4 Data Analysis: Complete Tables and Data. 105
BIBLIOGRAPHY................................................124
Vll


TABLES
Table 4.1 Work History of All Female Respondents and All Mothers*
of Respondents from GSS 1973 and 1998................ 59
Table 4.2 Percent of Women Who Work Who Had Mothers Who
Worked* While They Were Growing Up Women 40 to 50
and 30 to 40, 1971-1978 and 1991-1998................ 60
Table 4.3 Years of Education of All Women and All Mothers
of Respondents from GSS 1973 and 1998................ 61
Table 4.4 Effects of Mothers' Years of Education on Occupational
Prestige Women 40 to 50 and 30 to 40 1972-1978.... 63
Table 4.5 Effects of Mothers' Years of Education on Occupational
Prestige Women 40 to 50 and 30 to 40 1991-1998.... 65
Table 4.6 Effects of Mothers' Occupational Prestige on Occupational
Prestige Women 40 to 50 and 30 to 40 1994-1998.... 67
Table 4.7 Correlation-Regression Analysis for the Relationship of
Mothers' Years of Education and Occupational Prestige
to Occupational Prestige Women 40 to 50 and 30 to 40
1994 to 1998....................................................... 68
Table 4.8 Correlation-Regression Analysis for the Relationship of
Mothers' Years of Education and Occupational Prestige
to Subjective Class Identity Women 40 to 50 and 30 to 40
1994 to 1998........................................................ 69
Table 4.9 Correlation-Regression Analysis for the Relationship of
Fathers' Years of Education and Occupational Prestige
to Occupational Prestige Women 40 to 50 and 30 to 40
1994 to 1998........................................................ 70
Vlll


Table 4.10 Correlation-Regression Analysis for the Relationship
of Fathers' Years of Education and Occupational Prestige
to Subjective Class Identity Women 40 to 50 and 30 to 40
1994 to 1998............................................ 70
Table 4.11 Correlation-Regression Analysis for the Relationship
of Spouses' Years of Education and Occupational Prestige
to Occupational Prestige Women 40 to 50 and 30 to 40
1994 to 1998............................................. 71
Table 4.12 Correlation-Regression Analysis for the Relationship
of Spouses' Years of Education and Occupational Prestige
to Subjective Class Identity Women 40 to 50 and 30 to 40
1994 to 1998............................................. 72
Table 4.13 Correlation-Regression Analysis for the Relationship of
Mothers', Fathers' and Spouses' Years of Education and
Occupational Prestige to Occupational Prestige
Women 40 to 50 1994-1998............................................... 73
Table 4.14 Correlation-Regression Analysis for the Relationship of
Mothers', Fathers', and Spouses' Years of Education and
Occupational Prestige to Occupational Prestige
Women 30 to 40 1994-1998............................................... 74
Table 4.15 Correlation-Regression Analysis for the Relationship
of Mothers' and Fathers' Years of Education and
Occupational Prestige to Occupational Prestige
Women 40 to 50 1994-1998.............................................. 75
Table 4.16 Correlation-Regression Analysis for the Relationship
of Mothers' and Fathers' Years of Education and
Occupational Prestige to Occupational Prestige
Women 30 to 40 1994-1998.............................................. 76
Table 4.17 Correlation-Regression Analysis for the Relationship
of Mothers' and Fathers' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 40 to 50 1994-1998................................ 77
ix


Table 4.18 Correlation-Regression Analysis for the Relationship
of Mothers' and Fathers' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 30 to 40 1994-1998............................... 77
Table 4.19 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses', and Women's Occupational
Prestige to Subjective Class Identity Women 40 to 50
1994-1998............................................... 79
Table 4.20 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses' and Women's Occupational
Prestige to the Subjective Class Identity of Women 30 to 40
1994-1998............................................... 79
Table 4.21 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses', and Women's Years
of Education and Occupational Prestige to Subjective
Class Identity Women 40 to 50 1994-1998............................... 81
Table 4.22 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses', and Women's
Years of Education and Occupational Prestige to
Subjective Class Identity Women 30 to 40
1994 to 1998........................................................... 82
Table 4.23 Correlation-Regression Analysis for the Relationship
of Women's and Spouses' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 40 to 50 1972-1978............................................... 84
Table 4.24 Correlation-Regression Analysis for the Relationship
of Women's and Spouses' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 30 to 40 1972-1978............................................... 85
Table 4.25 Correlation-Regression Analysis for the Relationship
of Women's and Spouses' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 40 to 50 1991-1998.............................................. 85
x


Table 4.26 Correlation-Regression Analysis for the Relationship
of Women's and Spouses' Years of Education and
Occupational Prestige to Subjective Class Identity
Women 30 to 40 1991-1998.............................................. 86
Table 4.27 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses', and Men's Years of
Education and Occupational Prestige to Subjective
Class Identity Men 40-50, 1994-1998................................... 88
Table 4.28 Correlation-Regression Analysis for the Relationship
of Mothers', Fathers', Spouses', and Men's Years of
Education and Occupational Prestige to Subjective
Class Identity Men 30 to 40 1994-1998................................. 89
Table 4.29 Correlation-Regression Analysis for the Relationship
of Men's and Spouses' Years of Education and Occupational
Prestige to Subjective Class Identity Men 40 to 50
1972-1978.............................................. 90
Table 4.30 Correlation-Regression Analysis for the Relationship
of Men's and Spouses' Years of Education and Occupational
Prestige to Subjective Class Identity Men 30 to 40
1972-1978................................................ 91
Table 4.31 Correlation-Regression Analysis for the Relationship
of Men's and Spouses' Years of Education and Occupational
Prestige to Subjective Class Identity Men 40 to 50
1991-1998................................................ 92
Table 4.32 Correlation-Regression Analysis for the Relationship
of Men's and Spouses' Years of Education and Occupational
Prestige to Subjective Class Identity Men 30 to 40
1991-1998................................................ 92
xi


CHAPTER 1
INTRODUCTION
With all of the many indexes for measuring occupational prestige and
status that have been developed (Hollingshead 1949, Hodge, Rossi and Seigel
1964, Blau and Duncan 1967), there is a continuing failure to resolve the social
status of individuals comparative to gender. Although gender issues have been a
focus in Status Attainment Theory, there have been only weak efforts made to
include separate data on females. Nearly all of the social stratification indexes
used to measure individual and family social position are based on the supposition
that the family is the unit of measurement and the data to be used are information
gathered about the male head-of-household.
The assumptions made in stratification studies continue to exclude women
independent of their relationship to men. Those assumptions are, 1) that the
family is the unit of measurement in social stratification theory, 2) that class
position of the family is determined by the status of male head of family, 3) that
class position of a female is determined by the status of the male head of the
family of which she is a member, and her status is the same as the male. (Acker
1973)
1


Conventional Social Stratification Theory assumes that women can have
their own status only when they are not attached to a family with a male head of
household. However, in the last half of the Twentieth Century, many
demographic and economic changes have affected the social status of women.
Since the feminist movement in the 1960s, there is increased interest in exploring
women's issues, and studies have found numerous elements that should be
included when measuring women's social position, such as, changes in family
composition and size, increased educational attainment, full time participation in
the labor force, higher occupational mobility, gender differences in occupations,
equal pay for equal work issues, as well as a socially acceptable decrease in male
obligation to financially care for and support women. These areas of study are
important cultural changes that should be considered when measuring individual
social status separate from a woman's husband's class identity.
Let us look at three of these issues. First, the definition of family has
changed radically in recent years. The conventional view for measuring women's
social stratification does not address these changes in family composition. The
traditional nuclear family of husband/wage earner, housewife/mother, and
children all living in the same household, while still the majority of households, is
no longer the reality for many families in the United States. Since the 1960 U. S.
Census, the number of female-headed households has almost doubled from
2


9.8 percent to 17.6 percent. Women today are less likely to marry, more likely to
marry later, and more likely to divorce, according to the 1990 U. S. Census,
which also shows that children are five times more likely to be bom to an unwed
mother, and almost three times more likely to live in a female-headed household
than they were in 1960 (Gilbert and Kahl 1993, p. 290). While this change is due
in part to the greater tolerance of unwed motherhood and divorce, it is,
nevertheless, a change in family composition that affects family social position.
Second, paid employment and income reduces a woman's dependence on
her husband's social class position when identifying her own class position. As a
womans income increases, both in absolute terms and in relation to her
husbands income, she may rely more on her own situation to define for class
identity. (Baxter 1994, p. 222) The percentage of employed married women has
risen from about 25% in 1950 to more than 50% by 1985, and over 60% by the
year 2000. (U. S. Census) Full time paid employment would give women a
different perspective of social position than it does for women who work part time
or not at all.
Third, although the marital selection process today places more emphasis
on educational homogamy (the attitudes about and aspirations for educational
attainment that have become intergenerational characteristics of social position) a
number of studies (Baxter 1994, Abbott 1987, Jackman and Jackman 1983,
3


Hyman et. al., 1975, Kalmijn 1991) show that a woman's educational attainment
is important to her in determining her social position. Jackman and Jackman
found that a wife's level of education was a better predictor of her class
identification than was her husbands educational attainment. According to
Baxter, the more education and the higher occupational prestige a woman has the
more likely she is to decide her social position independently from her husband.
Baxter suggested, "...that husband's class alone provides an incomplete account of
subjective class identity..." (p. 233) In her 1994 study, she showed that the
husbands themselves were more likely to determine their class position by
including their wife's employment status (p. 222-230), and yet, no
accommodation has been made to include women's social status indicators in the
indexes measuring family social class.
Haller (1981), Acker (1973, 1980), Simpson et. al. (1988), Lockwood
(1994), and Scanzoni (1978) are among those who have discussed methods to
include gender in measurement of social status. Haller (1981) maintains that the,
"...essence of social stratification concerns the intergenerational and
intragenerational reproduction...through homogamous marriage patterns and
status inheritance over families and generations." (789) He believed in the
possibility that social position may not be just, ...one marrying pair and its
children but a sequence of marital and familial units... (p. 779) This study will
4


demonstrate that this is so. However, Haller did not follow through on
intergenerational family social status as a possible avenue towards a more gender-
neutral measurement of social position, and even now in the year 2002, the
problem has not been resolved.
In books as recent as the late 1990s, such as Social Stratification (1996),
by Daniel W. Rossides, gender inclusion measurement in social stratification is
not directly addressed. In Social Class and Stratification: Classic Statements and
Theoretical Debates (1998), David Lockwood points out that when discussing the
disadvantages of the continuing use of the conventional method for measuring
social stratification, The fact that something should be of concern to the Equal
Opportunities Commission does not thereby guarantee its sociological relevance.
(p. 195) He suggests that occupational prestige ranking is a reliable method for
measuring social position because, for the most part, occupational prestige is
sex-neutral." By sex-neutral he means, that the subjective ranking of status of
occupation is indifferent to whether a male or a female fills a job. This is not to
imply that the various occupations themselves are sex-neutral. In studies of job
prestige, the rating system is highly subjective and jobs held by women are
usually rated lower than those jobs held by men. We know that women are
represented exceptionally high in some of the lower middle class occupations,
5


such as the service and clerical sectors, and oft times, the higher the percentage of
women in a job, the lower its rating.
In another study, Scanzoni (1978) discusses the dilemma of how to
integrate gender differences into class stratification. He felt that combined
income could be used as a measure of family social position, but found that the
strongest predictor of a couple's social position was a combined score made up of
"external resources." (p. 67) Scanzoni defined external resources as, "skills or
capabilities that generate goal attainment in systems outside the family, especially
the occupational system..." (p. 25) He was also speaking of intangible innate
leadership and organizational skills. These intangible skills enabled a family to
utilize their resources to attain and maintain higher social position.
Joan Acker, who has had an abiding interest in women and stratification
since the 1970s makes a case for using the individual rather than the family as the
unit of measurement and for finding a method to cross-reference the data
collected on husbands and wives, but she did not devise a method for cross-
referencing data.
It has become imperative to find a valid, replicable measurement of
marriage and gender differences that could be incorporated into stratification
research. Along with women's increasingly independent social class indictors,
there are unique features and kin influences of family-of-origin that affect
6


individual social position that could give a more accurate picture of social
position of females besides husbands' class location. While it may not completely
explain women's social position, one possibility for measuring womens social
position is through mothers' status attainment indicators and the intergenerational
occupational mobility that women share with their mothers.
Using more information about mothers to determine social class would
provide the benefits of a better measure of socio-economic status by including the
mothers' occupation rather than just fathers' occupation. Research shows that
when a mother works, her daughter is more likely to work, to work continuously
and to choose an occupation that is less typically female. (Rosenfeld, p. 37)
Mothers' occupation represents an adult role model, particularly to daughters,
which could have an effect on the occupational choices of all children.
Women should insist that their input be counted. That it is still not so,
suggests that we have not "come a long way baby," and that there are underlying
factors that create problems for changing how social stratification is measured.
Among those factors are, first, many of the studies on social class positioning are
done by asking the respondents own opinion of their social class but go no
further. Unless, as Scanzoni (1978) demonstrates, women are questioned about
how their real or perceived ideas of their social class affects their ranking, it may
be that women's culturally socialized subjectivity about gender equality interferes
7


with their answers. Second, using data that measures social position of the male
head of household alone simplifies the management of resources and funding
from government agencies and other organizations. Third, there are those, like
Goldthorpe, who are complacent about the existing methods of measuring social
status. Their social stratification research reflects their failure to adapt to the
changes in attitude towards gender and status. For this reason, the validity and
continuing application of prior analysis and earlier conclusions of social
stratification using the family unit with only data of the male head of household is
debatable. While professionally sociologists agree that modifications need to be
made in how social stratification is measured, allowing for the independent status
that women have achieved, the modifications have yet to be done.
Inquiry into social stratification should not ignore the intergenerational
and intragenerational patterns of reproduction of social status. If, beyond certain
gender related jobs, who is doing the job does not affect the prestige of the job,
then Blau and Duncan's Socio-Economic Index could continue to be an accurate
assessment of an individuals social position. Measuring class status by family
unit remains a viable option, but needs to be expanded to include the
intergenerational characteristics that Blau and Duncan observed. This thesis
asserts that the concept of social class position cannot be understood apart from
the educational and occupational achievements of family of origin. Because of
8


the strong socializing influence that mothers have on their children, mothers are
an important feature in measuring social status. Including mothers' work status,
years of education, and occupational prestige to measure women's social position
might prove to be a more accurate indicator of social status than now used. In this
paper, characteristics of mothers' social position, such as years of education and
occupational prestige are utilized to examine how these indicators affect women's
social position through women's years of education, occupational prestige, and
subjective class identification.
9


CHAPTER 2
LITERATURE REVIEW
A Brief Historical Overview
Social stratification, an individual's position in his or her society and how
that position is achieved or ascribed was, early on, an important topic of
sociological debate. Emile Durkheim, the earliest structural-functional
sociological thinker proposed that as societies progress, they also evolve, and this
evolution moved societies toward more social complexity and differentiation.
Complex societies became increasingly characterized by diverse and specialized
roles for individuals. Durkheim proposed that much of that diversity was the
result of occupational specialization. However, from occupational specialization
there developed certain rights, such as the right to own property, to control labor,
and to receive political favor. These rights eventually became a part of an
individual's on-going social position.
Durkheim believed that social equality and opportunity would be the result
of occupational opportunity, but to the contrary, the social characteristics he
thought would create equality are the same characteristics that created distinct
social classes. Stratification formed because of the access individuals had or did
10


not have, through educational and occupational achievement to wealth and power,
and through ascribed characteristics, such as religion and ethnicity. Rather than
creating equality, the economics of occupational specialization created social
stratification with resulting inequalities. Durkheim did not accept that societies
were economic systems with inherent inequalities and his hope of equality was
simply idealistic dreaming. Were it not for Marxian Conflict Theory, social
stratification might not have focused almost exclusively on the socio-economic
inequalities of class, and instead focused on the social structures and functions of
class.
Karl Marx (1818-1883) and Max Weber (1864-1920) expanded on the
economic aspects of society and class. To Marx the economic structure created
divisions of labor and ownership of property that caused class formation. Weber
agreed with Marx that there were economic causes in the formation of social class
differences in society, but he elaborated on the reasons for class differences by
proposing that there were also non-economic, socio-cultural factors that affected
social stratification. Some of these socio-cultural influences are the social and
cultural capital that comes from family beliefs and values, and access to political
and legal influence. These socio-cultural characteristics tend to create boundaries
that restrict others from entering one's own social class as well as inhibiting one's
involvement with other classes.
11


To the economic factors of class, that affect social position, Weber added
'status,' cultural influences that also affect social position. According to Weber, it
was when the socio-cultural power of status was perpetuated generationally that
social stratification developed. It is important to note, that the early sociological
theorists were convinced that social stratification was an intergenerational
phenomenon. In recent years, for the most part, this has been ignored when
collecting data on social stratification.
The Oxford Dictionary of Sociology defines social stratification as,
. .systematic inequalities between groups of people, which arises as the
unintended consequences of social processes and relationships. (1998, p. 643)
The study of social stratification focuses on the differences between statuses, and
the openness between statuses in a society. According to Matthijs Kalmijn, "...the
openness of society is...(measured by)...how much people from different status
groups interact on the basis of equality..." (1991, p. 497)
Social stratification has been examined by a number Twentieth Century
theorists, including P. A. Sorokin (1927), Erin Olin Wright (1987), Kingsley
Davis and Wilbert E. Moore (1945), Gerhard Lenski (1966), Anthony Giddens
(1973), Peter Blau and Otis Dudley Duncan (1967). They have analyzed social
stratification from several differing perspectives. These are: the economic
perspective which includes occupation, income and wealth (Wright, Lenski,
12


Giddens); the status perspective which includes personal prestige, associations
and socialization (Kingsley, Davis and Moore, Giddens); the political perspective
which includes power and class consciousness (Lenski, Wright); and the social
mobility perspective (Sorokin, Blau and Duncan).
Measuring Social Stratification
The most definitive of the recent work that measures social stratification is
that of Peter Blau and Otis Dudley Duncan, with the publication of their book,
The American Occupational Structure (1967). Their understanding of social
attainment dynamics, presumed that social stratification is a handed-down,
intergenerational social trait continued by, what they perceived as the most
important variable, occupational prestige. Blau and Duncan proposed that
individual occupational position is a good measure of an individual social
position. The occupational prestige measurement they used was based on public
opinion of occupation, and because of general subjective perceptions of what is
considered an 'important' job and what is an 'unimportant' job, there is some bias
built into the measurement. Even the wording used for an occupation can
influence the prestige of the occupation. For example, the job, druggist or
pharmacist, even though the same, are subjectively seen as pharmacist being a
more important prestigious occupation than druggist. (Fussell 1983 p. 161) The
13


prestige of an occupation is more or less measured by how much power, trust, and
authority the occupation gives an individual, and to some extent, this is separate
from the income and educational indicators of social position. Fussell points out
that, "the degree of supervision" one receives or gives in an occupation may be a
better measurement of occupational status than either income or education.
(p. 48)
Blau and Duncans theory of social mobility is notable, because they were
able to devise a quantitative methodology for measuring social position that is still
in use today. In 1967, using education and income, they created the "Socio-
economic Index of All Occupations" (SEI). This index has proved to be
extremely reliable measurement of ranking prestige of occupations. They
theorized that individual social position had its origins in: (1) The social position
or class that an occupation is in; (2) Ascription, the ability to move between
classes based on social barriers such as race, ethnicity and gender; (3)
Intergenerational mobility, a relationship between the individuals social position
to that of the parents, and; (4) Intragenerational mobility, how individuals own
work status shifts them into different social positions over time.
Blau and Duncan considered that attaining status might be an ongoing
sequence of events, and that most occupational prestige and social position can be
perpetuated intergenerationally by the ability to acquire education and assets.
14


This perpetuation becomes a two edged sword when we realize that the ease or
i
difficulty of acquiring education and assets depends upon the social position that
an individual already possesses. While they conceded that social position was
intergenerational, their study was limited to father and son generations only.
Using the SEI to demonstrate social mobility, which is explained as, "The
movement, usually of individuals but some times of whole groups, between
different positions within the system of social stratification..." (Oxford, p. 422)
Blau and Duncan used regression analysis to find a correlation that explained to
what degree sons' social position was related to fathers'. The independent
background variables they used for their analysis were fathers' education and
fathers' occupation. They explored how fathers' occupational position affects the
occupational position of sons. If, as they hypothesized, status attainment was an
evolving condition, then examining sons' education, sons' first, and sons' current
occupation as dependent variables, would show the longitudinal changes that they
predicted. Measuring along a time line beginning with the fathers' education,
fathers' occupation when the son was sixteen, the number of years of the sons'
education, the prestige of the sons' first job, and the prestige of the sons' current
job, they found an intergenerational correlation. Blau and Duncan's study
explained that the social status influence of one generation on the next was a
sequence of events over time. They showed that by knowing fathers' occupational
15


position and educational attainment one could predict with reasonable accuracy
the occupational position of sons.
Social attainment in American society is not entirely explained by the
influence of one generation's education on the next generation's education and
occupation. It is important to point out that this effect does not relate only to
obtaining education, but relates also to "which" education is acquired. The school
attended by the fathers as well as the sons makes an enormous difference in how
the education is advantaged with the subsequent occupational prestige and social
position. There are also other difficult to measure indicators of status position
such as political stance and social connections. Going a step beyond this,
Gruskey and Sorensen, make a case for measuring social status by taking
"...contemporary patterns of collective action..." into account, such as trade unions
and associations, rather than just, "...aggregating technically similar
occupations..." (1998 p. 1224)
Other studies replicating and expanding upon Blau and Duncans work
followed on the heels of their study. One replication, the "Wisconsin Socio-
Psychological Model of Socioeconomic Achievement" by Sewell and Hauser
(1972) used in addition to fathers' education and occupation, background
characteristics such as fathers' income, mothers' education and family income.
The Wisconsin analysis showed that there was a significant effect of mothers'
16


education and fathers' occupation, income, and education on sons' occupation
similar to Blau and Duncan's original study. Other studies using variables such as
educational and occupational aspirations and peer interaction help to give further
indication of the influences on status attainment. These studies confirmed that
intergenerational features of family-of-origin were decisive influences on
individual social status. Unfortunately, today the collection of data on social
stratification primarily uses only indicators for individual education, occupation,
and income.
Social Stratification Measurement and Women
Studies replicating Blau and Duncan were conducted using education,
occupation and income data on the American male and give a reasonable and
reliably accurate assessment of the socio-economic status of the male population,
but not for the female population. No discussion of social stratification and
gender would be complete without including work done by John H. Goldthorpe,
particularly his 1983 paper, "Women and Class Analysis: In Defence of the
Conventional View. Goldthorpe has been adamant that occupational position of
the male head-of-household is the best measure of social position for females as
well. Even into the 1990s, he persisted in being one of those who emphasized the
entrenched structure of class and failed to account for the social changes of the
17


last several decades. In his 1983 study, he vigorously defended the position that
the family is the best unit of measurement for social stratification. He proposed
that since there were continuing, universal gender issues such as division of
household labor and availability of employment opportunities; and because
families pool their resources and share consumption patterns, class position
should be designated according to husbands' status characteristics.
This conventional viewpoint goes back to Durkheim's Structural-
Functional Perspective, which maintains that all social institutions, including
marriage, have particular purpose for maintaining the balance in society. From
the theorizing of Parsons, Goldthorpe points to three distinct reasons for support
of the functional perspective. He relates, 1) that the family must be considered a
single unit for the solidarity of its members, 2) that there needs to be a basic
equality of family members to maintain social position and, 3) that in most
societies, only one family member is able to have a total commitment to the
occupational system, (p. 466) His reasoning was that gender inequality is not the
cause but the reason to support the conventional view. He maintains that by using
the male head-of-household to measure status, women are actually elevated to a
higher status position than they would otherwise be if measured on their own
socio-economic merit, (p. 469) Goldthorpe interpreted data from several studies
18


to mean that even if a woman was employed she was still dependent upon her
husband. (1983 p. 468)
The structural functional point of view helps to explain historically why
the social position of the family has always been fixed by the status of the male as
head of family; why it is assumed that females live in a family headed by a male
and; why a female's status remains the same as the male head of family. This
perspective seems no longer viable when we consider the major social changes
that have occurred that affect women. Unfortunately, the continuing use of
Goldthorpe's essay as the gold standard of support for the conventional view is
outmoded when we consider that it was published in 1983 and the data were from
a previous study done a decade earlier in the mid 1970s.
The real progress toward equality for women in the United States began in
the early part of the Twentieth Century. Females were gradually gaining
autonomy from their fathers or husbands. They were allowed to own property, to
vote, and judged capable of raising and supporting their children. Back then, no
one considered the possibility that women could do all this and still hold a job.
Until then, women from the day of their birth were considered the 'property' of
their father and continued to be a part of their father's household until they
married, when they became the 'property' of their husband. If women were not
allowed to own property or vote, and few had an occupation of their own, there
19


was little reason to include data about women in any measure of social class. By
the end of the Twentieth Centuiy however, a majority of women worked and
many had educational and occupational levels equal to their husbands'.
The late Industrial Revolution affected women and employment in two
ways. First, supposedly women were freed from the overwhelming burden of
household maintenance with the development of modem appliances, such as
refrigerators, electric stoves, and washing machines. Second, the industrial
revolution needed the influx of large numbers of workers to operate
manufacturing machinery and women were accepted as factory laborers. Large
numbers of women, as wage earners, is a relatively new concept in the United
States. In 1890 less than 5% of manied women worked. Even fifty years later in
1940, the number was still only 16% (Davis and Robinson 1988, p.104). By
1968, the number had risen to 35.5% (De Jong, et al. 1971, p. 1033), and by the
year 2000 over 61% of women were in the labor force. (U. S. Census)
Viewed in this light, it is understandable why social stratification studies
dismissed the socio-economic position of women. However, the perception of the
family as a single unit has become an antiquated notion by our modem
assessment of what constitutes a family unit. Recent studies show the gender gap
as narrowing but as Gurin says, .the economic fates and claims to prestige of
men and women are inextricably intertwined. (p. 145) In the past, ascribed
20


characteristics, such as family connections, had the greatest effect upon whom
one married, but in the last half of the Twentieth Century marital choice for both
men and women in the United States changed to a preference for certain achieved
characteristics. Educational attainment is an achieved characteristic that has had
great impact. In a 1975 study, Hyman et. al., showed there is a negative
relationship between educational attainment and choice of marriage partner. He
explained that as a person's educational attainment increases, the chances of that
person marrying someone with low educational attainment decreases, even if they
have similarities in social class.
In "Status Homogamy in the United States," (1991) Matthijs Kalmijn also
showed that ascriptive marriage partner choice for individuals used to be to marry
someone from one's own social class, but by comparing studies of status
homogamy he showed that "...the correlation between spouses' education is
stronger than the correlation between spouses' class origins." (p. 500) Educational
institutions not only provide couples with educational equity, they also have an
effect on values, attitudinal characteristics, and life-style preferences. Kalmijn
found that the association between education and marriage partner selection
increased for all cohorts in his study. It is reasonable to assume that educational
attainment and the subsequent occupational prestige have become an important
factor in the process by which males and females choose a marriage partner with
21


its consequent social status. A recent poll from the E.W. Scripps School of
Journalism at Ohio University shows a direct relationship between education and
marriage. (Hargrove p. 75) The more education people have the more likely they
are to be married. For males as well as females, two-thirds of those with a college
education were married, while less than half of those with only a high school
education were married. Educational attainment as a characteristic of social
position has consistently been important for men, it seems it is now important for
women also. In 2000, the number of women who have at least a college degree
though rising still does not equal the number of degrees obtained by men. In
1970, for every ten males having at least a college degree, six females had at least
a college degree. In the year 2000, for every 10 males who have a college degree,
there were approximately eight females who have at least a college degree. (U. S.
Census)
With all the gender based social changes that have taken place in the last
40 years, there has been some interest in studying how women's roles affect their
social stratification (Acker 1978 and 1980, Grusky and Sorensen 1998, Baxter
1994, Haller 1981, Scanzoni 1978, Sorensen 1994, Davis and Robinson 1988).
All agree that how social stratification is measured needs to be modified to reflect
the independent status that women have obtained. In Davis and Robinsons 1988
study of the subjective class identity of married men and women, they used three
22


models of identity. In the "independence model, social class is identified by
individual characteristics of both men and women separately. The sharing
model gives equal weight to the characteristics of both spouses. The borrowing
model determines class by only the characteristics of the spouse, usually the male.
This is seen,
"...as a continuum ranging from ones own characteristics as the sole
determinant of ones class position...through joint determinants that
include spousal characteristics, to viewing ones own characteristics...as,
unimportant relative to those of a spouse." (p. 105)
They found that men were gradually becoming more accepting of the
independence model and women were becoming more inclined to accept the
sharing model rather than the borrowing model of previous studies. This
shows that it is not only changes in gender role attitudes but also womens recent
social and economic autonomy and newly discovered awareness of their position
that gives them awareness of socio-economic equality.
Gender consciousness for women has moved their perceptions to
questioning, ...the legitimacy of gender disparities... (Gurin, p. 156) With
women using their successes as role models, they are no longer accepting that
men are better qualified for particular jobs or are more ambitious than women.
That men accept the "independent" model shows they also have become more
gender conscious. That is, while the men may not be crediting spouses with
23


contributing to the men's social status, they do credit the women with contributing
to their own social status. Gurin found that men have changed their perception of
power so much that by 1983 there was little difference of opinion between men
and women, (p. 160)
Gender consciousness also encompasses some amazingly fast changes in
social attitudes and role expectations for women in recent decades. The social
acceptance of non-traditional female behavior has changed the mother/adolescent
daughter relationship. Tallichet and Willits (1986) found that the higher a
mother's educational attainment, the more liberal were her attitudes. When the
daughters matured, they were more likely to have higher educational attainment,
were more likely to work, and were less likely to marry young. That a woman
should derive her own status from her own accomplishments seems to be an idea
whose time has come.
There have been numerous studies suggesting how it might be possible to
measure womens social position separately from mens, but none of them
incorporate intergenerational family-of-origin characteristics. Using the Symbolic
Interaction Perspective, Max Haller (1981) suggested that to understand the use of
family as the fundamental unit of social stratification, one must first understand
that marriage itself is a stratification relationship and next, must understand how
this relationship is affected by the separate "acting units", the husband and the
24


wife. (p. 775) The way to do this, he proposed, is to divide marital homogamy in
social position measurement into two separate variable classifications, social
stratification and social class formation. Social class formation becomes the
public sphere of workers and managers, production and distribution, solidarity
and competition. Social stratification then becomes the private sphere of
individual and collective identity, relationships, and interactions. In a
homogamous marriage the couple would show a preference for sharing a wide
range of characteristics such as intelligence, values, religion, race, and social
class. Haller points out that couples in homogamous marriages are less likely to
divorce. A likely affect of less divorce would be the perpetuation of
intergenerational family social status.
In an article published in 1980, Joan Acker reviews literature dealing with
women and stratification. For her, existing theories do not adequately explain
women's social position. She felt that to separate research into two types, such as
Haller suggested would only create more confusion about where women stand in
relation to social class. Others (Chafetz, 1974; Walum, 1977; Blumburg, 1978)
have proposed separating stratification into sex and class divisions, but Acker was
concerned whether this perspective could give an accurate picture of the socio-
economic position of women, because theories of sexual inequality and socio-
economic inequality though defined by different issues can not necessarily be
25


separated in social stratification. As she points out, "...sex stratification always
involves economic and power inequalities..., that are a product of the existing
social system, (p. 26)
Other stratification models Acker discusses are the Dual-Economy/Labor-
Segmentation Theory, Marxist Market Economy Theory, the Feminist Paradigm,
and Social Mobility Theory. Dual-Economy Labor-Segmentation Theory
explains gender differences in social standing as differences in the core and
periphery sectors of the economy, meaning that whether an individuals
occupation is considered white collar or blue collar or has authority or no
authority makes a difference in society's perception of the subjective value of
that individual. Periphery labor may be perceived as having less value than it
really does and core labor perceived as having more value than is the reality. To
understand social status and gender, we need to understand that many of the
female-centric occupations tend to be in the periphery, which have lower
occupational prestige.
Marxist Market Economy Theory proposes that women's position in the
class structure is the result of capitalism needing a reserve labor pool and that
labor pool is unequally made up of women. The thinking is that if there are more
workers than the system can absorb, then workers have less value in the labor
26


market. The large influx of women into the service type of jobs and the low pay
they receive is an excellent example.
The Feminist Paradigm expects that all measure of social position should
be on an individual basis regardless of marital status. However, using the
Feminist Paradigm for measuring social status and completely abandoning the
idea of the family as the unit for stratification and class analysis, presents its own
difficulties. Measuring each individual separately according to his or her
occupational prestige would not provide an accurate measure of family class
position, a measurement needed for understanding the distribution of resources.
Using information about both husbands and wife's occupational position
would be a start towards a combined measure of social position, but it is difficult
to rate occupations in such a way that the combined score would accurately
represent the husbands and the wifes family social position. For example, using
the three divisions of the socio-economic index variable of occupational prestige
created for the data exploration in this study (10-36=low SEI, 37-67=middle SEI,
and 68-89=high SEI), if the husband is a dentist with SEI of 74 and the wife is a
social worker with SEI of 52, the mean becomes SEI 63 or a middle occupational
prestige. This is probably not an accurate representation of the family's social
position, although, because studies show that husband's occupational prestige
27


score has more effect on the perceived family social status than the wife's, it
might be possible to weight the husband's SEI score to show the greater effect.
Ideally, some type of modification to the conventional way is needed to
determine a family's social position. Sorensen (1994) suggests two possibilities, a
"head-of-household" form of measurement, and a "joint classification" form of
measurement. "Head-of-household" measurement, while similar to the
conventional view, could be modified to designate as head-of-household, "...the
person with the dominant occupational position," (p. 30) or designate the person
who has the, "...greater influence on the family." (p. 40) Her "joint classification"
model would, "...combine information about both husband's and wife's
occupational class into a joint measure of family class position..." (p. 41)
Of all of the proposals for a dual measurement of family social class, John
Scanzoni may have come the closest to discovering spousal perceptions of social
class, except that like others, he does not include family-of-origin. In his book,
Sex Roles. Women's Work and Marital Conflict (1978), he uses secondary data
from a previous study (Laumann and Senter, 1976) to show how wives'
employment and income can affect subjective class placement. Using as variables
only information about husbands (the conventional measurement of family social
status), working and non-working women were asked to decide social class solely
on information about their husbands. Husbands' income was the variable that had
28


the most influence on selection of class position by wives, followed by job
prestige and standard of living (economic satisfaction). However, after including
the women's employment and income, women were able to distinguish between
social position attained by their husband's contribution alone and the higher social
position attained when their own contributions was included, (p. 68)
Subjective Class Identification
The existence of class has its foundation in Marxist Theory, but class
distinctions are not as clear-cut and obvious as Marx predicted they would
become in modem industrial societies. Although there are large differences in
class just as Marx expected would occur, between owners of the means of
production and workers, post-industrial American class status is chiefly measured
by three socio-economic indicators. They are, 1) individual years of formal
education from none through post graduate years, 2) occupational prestige score
as measured by any one of the accepted indexes (this study uses Blau and
Duncan's Socio-Economic Index of All Occupations, known as SEI) and, 3)
income, usually an ordinal measurement of income defined by dollar amount
categories from low to progressively higher amounts. These three indictors are
used primarily because their characteristics are so easily measured quantitatively.
In reality, class identification is almost entirely a subjective interpretation of
29


where one fits into the social hierarchy. Individuals make personal choices about
where they themselves fit, and as much as we claim objectivity, our choices about
where others fit is quite subjective as well.
Richard Centers studied the subjective interpretation of social class in
1949, and Mary R. Jackman updated his study in 1979. When measuring social
class, one would expect that the class categories would have clear definitions; that
is, what is meant by upper class, middle class, working class, and lower class,
etc., but they do not. Jackman points out that there are undefined cultural
characteristics that, although are difficult to measure, such as beliefs and lifestyle
but are, nevertheless, subjectively used to define social class. This difficulty in
measuring intangible characteristics is almost entirely the reason that class
stratification has come to be measured by occupation, income and education
(1979, p. 459).
As Julie Mitchell explains, "...through out history, biological
differentiation of the sexes...and the division of labor..." (1998, p. 175) have
helped to explain the gender disparity that exists when measuring male and
female social status. The subjective nature of class identification through
occupation, education, and income has been dominated by male characteristics.
Identifying the social class of the female by the social class of the male has been
the customary way to measure family social class in our culture. This
30


conventional view has become flawed since women have begun to assess their
class position on their own merit.
Scanzoni shows that the influence of women working and the increased
family income has a significant effect on subjective class identification. In his
1978 study, women were asked if there was a, "...positive impact of wife working
on class..." When the women responded positively, they were asked to
subjectively assess what the difference in class would be. A new variable was
then created in which class position was based on the composite input of both
husband and wife. (p. 66) A mean score of 1.97 (high working class) was
obtained for subjective class position when only husbands' input was considered,
but this climbed to 2.22 (lower middle class) when joint input was used. Even
with non-working wives there was a positive influence on perceived impact on
lifestyle when asked what the effect would be if the woman was currently
employed. Other studies confirm that class identity is in part subjective
(Simpson, et. al. 1988 and Davis and Robinson 1988). Each found that if women
worked, they were less likely to borrow their class position from their husband.
Scanzoni goes on to speculate how a wife's income could effect household
class position. He proposed that the effects could involve consumption behavior,
wives using on the job skills to manage their household budget more successfully
to obtain status goods. For example, he suggests that wives of factory workers
31


who might consider themselves working class could use their money managing
skills, "...in such a way as to attain what they considered to be a middle-class
lifestyle." (63) The use of extra income could be used to aid their husband's
occupational activities such as entertaining work peers and to influence work
place superiors. Household status could also be affected by wives using their own
on-the-job work skills to advantage social position in situations outside the family
and work environments by creating social capital.
Social and Occupational Mobility of Women
Acker believes that to adequately measure social stratification, "...a sex
integrated treatment of class stratification..." (1980, p. 33) must be developed.
She sensed that the Social Mobility Perspective could have the most possibilities
for developing a gender-neutral measurement for social stratification. She says
that, In spite of differences in mobility patterns between the sexes, the most
consistent findings are that occupational and marital mobility patterns of women
are not much different from those of men..(p. 27)
Studies of social status as measured by intergenerational occupational
mobility have focused almost exclusively on fathers and sons. One study
explored what occupational mobility pattern could be expected by studying
fathers and daughters. This 1971 study by De Jong, Brawer, and Robin shows
32


that the occupational mobility between fathers and daughters is similar to that
between fathers and sons, and would suggest that there could also be similarities
between mothers and daughters that might be significant. They also point out that
if women are obtaining patterns of occupational mobility similar to men they
could be deriving similar levels of social status from their occupations.
Comparisons of occupational categories, as in a study done by Rachel Rosenfeld
in 1978, show that at that time, daughters did have a tendency to end up in
occupational categories similar to their mother's, but her study was limited
because her goal was to show sex similarities in occupational attainment between
mothers and fathers and their daughters. She was not pursuing alternative
methods of measuring socio-economic status.
Other studies explored the effect of husbands' occupational mobility on
women's mobility. In a study done in 1974, Tyree and Treas called this "marital
mobility." (p. 297) They found that women had a tendency to move from their
fathers' occupational category to a category similar to husbands' when they
married. This study shows that today, women are more likely to identify with
their mothers' occupational category than with their fathers'.
In "Five Decades of Assortative Mating," Robert Mares made an
interesting observation on choice of marriage partner. He proposed that women's
increasingly career oriented participation in the labor force may be changing
33


men's expectations of what constitutes a good marriage partner. He explains that,
"... if men increasingly see women as breadwinners as well as mothers and
homemakers...then men...will seek women who have the best earnings potential."
(1991, p. 17) This would be separate from a man's own earning potential, and
certainly have an effect on measuring social status. Other studies (Baxter 1994,
DiMaggio and Mohr 1985), show that there is a trend towards increased
educational assortative mating practices.
Another reason for educational homogamy in marriage could be
competition among men to marry women with good earnings potential brought
about by their educational attainment. Max Haller supports Mares when he
suggests that women with good earnings potential are being sought by men with
both high and low educational attainment, and given the choice, women would
most likely marry men who also had good earnings potential, thereby maintaining
or increasing their socially stratified class level. Haller goes on to say that
increased educational attainment for women also reduces, "...the need for relying
on marriage as an institution of maintenance and at the same time increases
expectations about a marital partnership." (Haller, p. 782)
The problem with past studies of social stratification is that they did not
explore new avenues for predicting women's status attainment. They used data on
fathers and husbands for measurement and even when data on mothers was used,
34


it was to compare mother/daughter job categories not to measure social status. It
seems obvious that the problem with measuring social stratification by using only
data about the male head-of-household and the family as the unit for measurement
does not go far enough to obtain an accurate measure of family social position.
To obtain an accurate measure family social status, we must cast the net wider.
Socialization of Children
If we limit our measurement of social status to the occupation, income,
and education of the head-of-household to obtain social position, but ignore the
on-going persistent family status over several generations, we ignore the
economic and cultural capital that increases one's ability to maintain social
position. Symbolic Interaction Theory can help to explain social position if we
include data on characteristics from family-of-origin. Symbolic Interactionism
focuses on the ways people give meanings to things in the world around them
through interaction with others. Those meanings are internalized and become a
part of the individual's social life. Studies of the socialization of children show
that, "...the intergenerational transmission of attitudes...and mother's attitudes in
particular, are significant predictors of (children's) attitudes..." (Bohannon 1999,
p. 173) Major studies of maternal behavior and social class have proven
conclusively that the mother is the primary socializing agent for her children. She
35


is the most important element in giving meaning to her child's world. It is
possible that mothers' social class also makes a difference in the methods of active
socialization the mothers use.
How do mothers' attitudes particularly affect their daughters? Studies of
parentally transmitted attitudes (Adams 1967, Barber 2000, Acock and Bengston
1978, Arditti, Godwin and Scanzoni 1991, Jennings and Niemi 1982, Rollins and
White 1982) have shown that daughters tend to internalize the attitudes of their
mothers. For example, Barber's study (2000) on parents and childbearing
suggests that the preference of when to have children is a socio-economic issue
based on the prior socialization of the parents. Those in the lower classes who
have less education, and non-working women prefer to marry young, have
children at a younger age, and to have larger families. This would affect the
eventual socio-economic choices of the children. Rollins and White (1982)
showed that mothers influence the attitudes about career choices of daughters as
young as 10 years old. When measuring influence of kin, Adams (1967) found
that daughters consider their mothers the "prime movers" in their success as
adults, (p. 369)
De Jong, et. al., point out, "...occupational mobility is in part a
consequence of continuity of employment..." (p. 1034) It is possible that because
of socialization, mothers' work history and occupation during children's growing
36


up would have an effect on the work history and occupation of the children,
particularly for daughters. An increased influence of maternal occupational
prestige on daughters could be explained by the amount of upward mobility
congruent with higher numbers of women in the work force. A study by Heyns
and Catsambis in 1986, suggests that mothers' work history is very important to
the achievement of children. They found that children's positive achievement was
not so much affected by whether the mother worked or not, but affected more by
the stable work history of the mother.
If we assume that parental attitudes about occupation and education are
internalized early in a child's life, then a mothers educational attainment and
work experience would probably affect her methods of teaching her child.
Employed mothers, especially those in high status occupations with greater job
satisfaction, could be expected to encourage high achievement in their children.
Such is the case according to Matthijs Kalmijn. In his study, "Mother's
Occupational Status and Children's Schooling" (1994), he found that a mother's
occupational status had a strong influence on her children's educational
attainment, independent of a father's occupation.
Mothers influence their daughters, and the daughters eventually influence
their husbands, so it is worth noting that studies of occupational achievement of
males (Rosen 1961; Mortimor and Lorence 1979; Heyns and Catsambis 1986;
37


Kalmijn 1994) show that maternal influence on sons is also significant enough
that it probably should be taken into account for all studies of achievement of
males as well as females. In "Family Structure and Achievement Motivation,"
Rosen showed that a mother who dominates the decision making process is
perceived as imposing her standards on boys, while fathers who are dominating
are perceived as imposing himself on his sons. (1961, p. 575) When mothers
make decisions they tend to try to enlist the cooperation of children rather than to
just coerce them, this could be why, "...mothers appear to promote the
development of achievement motivation in boys." (p. 577)
Other studies of boys and mothers show that mothers' employment has a
positive effect on sons if the mother is a high achiever as shown by her
occupational prestige. (Scanzoni, p. 345) In fact, mothers are so influential in
their children's educational and occupational success, studies show that single-
mother families, when employment status is taken into account, are second only
to two parent homes in significance when measuring a childs socio-economic
success. (Biblarz, et. al., p. 321)
When we understand the strong influence that mothers have on their
children, it becomes important to explore the effect mothers have on their
children's social status. Since studies show an association between mothers'
influence and occupation on sons as well as daughters, using data on mothers'
38


occupational prestige could be the additional indicator we have been looking for
to obtain a more accurate assessment of social stratification. I turn now to the
exploration of the social class of mothers as measured by her years of education
and occupational prestige, and how it affects the social class of daughters. At the
end, data on men and their mothers, fathers, and spouses will be briefly examined
to see if there is an additional effect on social class between these family members
and men.
39


CHAPTER 3
METHODOLOGY
To assess the affect that mothers have on women's social status, I explore
the following questions, 1) How has work status changed for women and their
mothers in the United States in the last three decades? 2) Is women's work status
affected by mothers' work history? 3) Has women's and mothers' educational
attainment changed in the last three decades? 4) Is women's occupational prestige
affected by mothers' years of education and occupational prestige? 5) Is women's
subjective class identity affected by the years of education and occupational
prestige of mothers?
If these indicators do affect women's occupational prestige, then it is
important to see if they remain significant compared with the effect that fathers'
and spouses' indicators have on women's social status, so the following inquiry is
made. 6) Is women's occupational prestige and subjective class identity affected
by the years of education and occupational prestige of mother, father and spouse?
(7) How is women's occupational prestige affected by the years of education, and
occupational prestige of only family-of-origin, the parents? 8) How is women's
subjective class identity affected by their own occupational prestige as well as the
40


years of education and occupational prestige of mothers, fathers and spouses? 9)
How is women's subjective class identity affected by only her own and spouses'
years of education and occupational prestige? 10) Is men's subjective class
identity affected by their own years of education and occupational prestige as well
as the years of education and occupational prestige of mothers, fathers, and
spouses? 11) How is men's subjective class identity affected by his own and
spouses' years of education and occupational prestige?
Data
For studying the effect mothers have on women's social class as measured
by their years of education, occupational prestige, and subjective class identity, I
selected 1972 through 1998 cumulative data from the General Social Survey. The
GSS is a survey asking questions about a wide variety of social issues.
The first year that the General Social Survey was conducted was 1972. It
has been conducted in the United States at more or less regular intervals by the
National Opinion Research Center in Chicago. GSS uses a national multistage
probability sample to the block level. At the block level quota sampling is used
based on sex, age, and employment status. (GSS Cumulative Codebook pg. 784)
The sample of participants is chosen carefully and thoroughly so that the results
are considered a representative and accurate assessment of the general American
41


population. Every year that the survey is conducted, between 1000 and 2000
English-speaking male and female adults 18 years of age and older are asked
questions in face-to-face interviews using the standard questionnaire method.
There are three types of questions in the survey. First, there are permanent
questions that appear every time the survey is conducted; second, there are
rotating questions done every two to three years; and third, there are occasional
questions prompted by current events in the year of the survey. Not all questions
are asked of all the interviewees. To facilitate the interviews and still acquire as
much data as possible, some questions are asked only of a sub-sample of
individuals.
Sample
To explore the affect that mothers have, over time, on the social position of
women, I selected a sample of females from an early time period, combining the 1972
through 1978 surveys, and from a late time period, combining the 1991 through 1998
surveys. The early and late time periods create sub-sets of women who have had
similar life experiences, but the sub-sets are also far enough apart in years to show the
effect of general cultural changes. Although the question about whether or not a
mother worked while the respondent was growing up was not asked in 1972,1 used
42


six years to maintain an adequate number of respondents. The later grouping includes
five years because there were no surveys conducted in 1992, 1995, or 1997.
I divided the sample of females into two birth cohorts, from the early and late
sub-sets. This created four birth cohorts in all, two between the ages of 40 and 50
years old and two between 30 and 40 years old. Birth cohorts are groups
characterized by common experiences. By selecting women who are 30 years old or
older, I can assume that they have been in the work force for a number of years and
that they have had experienced some intragenerational occupational mobility. In this
case, an early and a late birth cohort give a representation of not only the life
experiences and occupational history of the women in my sub-set but also of their
mothers by suggesting cohorts of the mothers. There are 21,417 female respondents
in the GSS data from 1972 through 1998 with 5137 females ages 30 through 40, and
3854 females ages 40 through 50 in years. The combined surveys for the early and
late groups yielded a sub-sample of 986 and 1434 women respectively 40 to 50 years
old. For women ages 30-40, the sub sample size is 1250 for the early group, and 1770
for the late group.
Because I was analyzing only women and their mothers, I did not focus on
whether female respondents had children or if they or their mothers were single or
married, excepting when looking for the effect that respondents' spouses' data
might have on their social position. Whether or not a woman was married or had
43


children might affect her social position, but was not a consideration in my
analysis. I also did not focus on any racial or ethnic differences amongst the
respondents. These finer details of the lives of women and their mothers would
be appropriate for further study of this topic.
Because I briefly explore the effect that mothers', fathers' and spouses'
social status indicators have on men, I use the same approach for sample selection
that I used in selecting the sub-sets of women. That is, 1)1 use the same two age
cohorts, men age 40-50 years and men age 30-40 years, and; 2) I use the same
year groupings, an early grouping, years 1972-1978 and a late grouping, years
1991-1998. The sample of males was taken from a total of 16,699 men in the
GSS from 1972 through 1998. There are 877 males age 40-50 in years 1972-1978
and 984 males age 30-40 in years 1972-1978. In the years 1991-1998 there are
1192 males age 40-50 and 1402 males age 30-40.
Variables and Indicators
Upon exploration of the variables available in the GSS that could be used to
measure female respondents social position, I found years of education, degree
attainment, income, occupational prestige, subjective class identity, marital status,
work status, and rank to have possible use in my study. I selected these variables as
useful because they are all relevant to social status. The social sciences primarily
44


measure status using three primary indicators. They are years of education,
occupational prestige, and income. These other variables listed, such as marital
status, work status, and rank are all affected by the three primary indicators. For
example, women's work status (part time or full time) can affect income, and income
affects social status. In most cases, higher social class is indicated by higher income.
Because this study is about the affect mothers have on womens social
position, of further interest are variables pertaining to respondents' mothers. In the
nearly 30-year history of the GSS, 18 questions have been asked that pertain to the
relationship between respondents and their mothers. Most of these questions are not
relevant to exploring mothers' effect on daughters' social position, such as "Is mother
still living?" Several questions of interest but only asked one or two times between
1972 and 1998 are questions about, 1) Mothers working and closeness of relationship
to child, 2) A comparison of the respondents and the parents standard of living and, 3)
The amount of influence that women have in our society.
Questions that were asked consistently from 1972 to 1998 that can be used to
explore the effects of mothers' social class indictors on women's social position
include, 1) What is mothers' work history, and did the mother work while respondent
was growing up? 2) What are mothers' years of education? 3) A third question of
importance for explaining the effects of mothers on women's social position is
45


mothers' occupational prestige, but respondents were not asked a question about
mother's occupation until 1994.
In studying mothers' influence on women's social position it is important to
make comparisons with the influence of fathers and spouses on womens social
position. Data about respondents' fathers' and spouses' education and occupation were
available for all years the GSS was conducted.
I subjectively projected that the mothers were between the ages of 20 and 30
years old when the respondents were bom. By projecting backwards, we can get
approximate years of birth for the mothers. For example, the birth years of the
mothers, for the older women 40-50, in the 1972 to 1978 group, would be about 1892
to 1918; and the birth years for the younger women 30-40 in the 1991-1998 group,
would be about 1921-1948. Although years of birth for the mothers is quite a wide
range, year of birth could have an effect on whether or not mothers worked, their
years of education, and occupational prestige.
Combining separate variables for respondents' and spouses' occupational
prestige was required to create a continuum of information. Respondents' and
spouses' occupational prestige is presented in two separate variables, PRESTIGE and
SPRES for surveys conducted 1972 through 1990 and PRESTG80 and SPRES80 for
surveys conducted 1988 through 1998. Leaving the coding the same, I copied the
46


data into one variable for respondents, PRESTALL and one variable for spouses,
SPRESALL.
Collapsing the occupational prestige variable for respondents was necessary
for manipulating the data in cross tabulation analysis. Comparing the Occupational
Classification Distributions (GSS 1972-1994 Cumulative Codebook, Appendix F,
p.871-889), to find three categories that are a reasonably precise measurement of
occupations that have low, middle, and high prestige, they were divided as, 10-
36=low prestige, 37-62=middle prestige, 63-89=high prestige. The following
exemplify the low, middle, and high categories. The break between occupational
prestige score 36 and 37 gives the occupations, clerical supervisors, counter clerks,
meter readers and clothing ironers for 36, while occupational prestige score 37
describes dental laboratory technicians, protective services occupations, office
machine repairers, and various types of machine operators. The break between
occupational prestige scores 62 and 63 gives such occupations as optometrists and
registered nurses at 62, and mathematical scientists and economists at a prestige score
of 63. This division did not distribute the data into categories with equal frequency
with the higher prestige category having the fewest number of cases.
Collapsing some of the other variables is also necessary to do cross tabulation
analysis. The years of education variables for respondent, and respondents' fathers,
mothers, and spouses are recoded from twenty-one into three categories. Combining
47


categories is necessary to obtain an adequate number of respondents in the higher
education category. This produces variables measured as: 1) less than high school
education, 2) high school graduate, and 3) at least one year of college. The variables
are now ordinal in nature and require that the proper measures of association be used.
For reasons that are not clear, the regression program seems unable to read correctly
the coding of years of education that began with zero. Once these numbers were
recoded into single digits, for example, one year of education from 01 to 1, regression
analysis proceeded normally.
The dependent variables are female respondents', 1) Work Status, defined
by whether she was working or had worked, 2) Years of education, used as both a
continuous variable (from none through 20 years of education) and as an ordinal
variable with three separate categories (less than high school, high school
graduate, some college), 3) Occupational prestige, as measured by the Blau and
Duncan SEI score, a subjective measure ranking occupations from 0 to 100
(although the lowest is 10 and the highest is 89) used as both a continuous and a
recoded ordinal variable and, 4) Subjective class identity, as measured by Richard
Centers, using four categories of class which are lower, working, middle, and
upper.
The independent variables are female respondents', 1) Mothers' work
history, as measured by whether the mother worked or did not work while
48


respondent was growing up, 2) Mothers', fathers', and spouses' occupational
prestige, as measured by the Blau and Duncan SEI score, a subjective measure
ranking occupations from 0 to 100 (although the lowest is 10 and the highest is
89) used as both a continuous and a recoded ordinal variable, 3) Mothers', fathers',
and spouses' years of education, used as both a continuous variable (from none
through 20 years of education) and as an ordinal variable with three separate
categories (less than high school, high school graduate, some college).
The grouping variables are, 1) Two specific year groups, 1972-1978 and
1991-1998 and, 2) Two birth cohorts, 40 to 50 year olds and 30 to 40 year olds.
For measuring the effects of mothers', fathers', and spouses' social class
indictors on men's occupational prestige and subjective class identity, I use the
same social class indicators used for females. These are: mothers', fathers', and
spouses' years of education and occupational prestige; as well as respondents'
years of education, occupational prestige, and subjective class identity. Where
needed these were recoded or combined into one variable in the same manner as
those for female respondents.
Method of Analysis
My hypothesis is that mothers' work history, years of education and
occupational prestige influence women's occupational prestige and subjective
49


class identity. This study is a systematic analysis of social class position of
women through her status attainment and intergenerational occupational mobility
as measured by mothers' work history, years of education, and occupational
prestige.
In my basic model to explore the relationship between mothers' and
women's social class, social position is operationalized by using the variables
work history, years of education, occupational prestige, and subjective class
identity that pertain to respondents and to mothers of respondents. Inclusion of
data on fathers' and spouses' years of education and occupational prestige is used
to assess the independent effect of mothers' data. Grouping variables, birth
cohort, and selected survey years, are needed in the analysis because of historical
changes in women's and work experience, educational attainment, and
occupational prestige in the last thirty years.
It is expected that mothers' work history, years of education, and
occupational prestige will all have a positive effect on the occupational prestige
and subjective class identity of women and that this would subsequently affect
women's social position. However, because numerous studies in the past argued
for the traditional measurement of social class that measures women's social class
by that of fathers and spouses (Goldthorpe, 1983; Sorensen, 1994; Baxter, 1994)
the possible effects of fathers' and spouses' years of education and occupational
50


prestige are investigated before determining the over all effect from the mothers
on the social class of women.
By first doing cross tabulation analysis, I will see if there is a relationship
between mothers' work history, years of education, and occupational prestige and
women's work history, years of education, occupational prestige, and subjective
class identity. The collapsed categories and new variables I created help reduce
the number of cells that do not have adequate data or would otherwise be empty,
affecting the validity of the results. Any relationships between mothers' years of
education and occupational prestige and women's years of education,
occupational prestige, and subjective class identity found in the cross tabulations,
will be compared in linear regression models to determine the strength of the
relationships and whether the relationship is positive or negative.
The relationship between men's occupational prestige and subjective class
identity and mothers', fathers', and spouses' years of education and occupational
prestige is briefly explored to help us assess the over all strengths and weaknesses
of the intergenerational indicators.
51


Limitations
Data Limitations
The question of how mothers influence the social position of women can
be answered only in part due to the confines of the GSS data set. There are, as
with any data set, limitations to how the data can be manipulated and the
information the data supplies. For my study, the data limitations found in the
1972 through 1998 surveys are:
1. As complete and representative as the GSS data set is, it is still an
example of the biases against women by the social sciences. It was only in 1994
that the GSS first asked a question about mothers' job and computed the
occupational prestige score. Until that year, occupational prestige score had been
measured for respondents, respondents' spouse and respondents' father only.
Having only three years of data on mothers' occupational prestige is a weakness in
my study. It would have been very helpful to have many more years of measuring
mothers' occupational prestige for a greater understanding of how mothers'
occupational prestige affects the social status of children. This problem can be
addressed in further studies using data where this information is supplied or by
collection of new data.
52


2. The GSS survey is administered only to English speakers, so the
opinions of non-English speakers are lacking in the surveys. I made no direct
attempt to include or exclude women of various races and ethnicity.
3. There seems to be no cross-referencing of respondents to see if other
family members have participated in the past. I had no way of knowing if any of
the women in my sample were related to each other but the effect would probably
be so minimal that it would not affect the data.
4. As with any survey that uses a random sample, there is error in
assuming the same percent of different individuals would answer the questions
the same as the sample. This sampling error, while not to be taken lightly, can
usually be ignored in this type of survey.
5. Because the GSS is a survey using a sample of the general population,
there can be some problem created in assuming the data can be applied to the
population as a whole. In most cases, it is safe to assume that the error would be
so minor that it is ignored and the conclusions reached from the data are viewed
as valid and applicable to the general population.
Other Limitations
1. The SEI prestige scoring system of Blau and Duncan, was created using
data on males alone, using a scoring system from a survey of subjective opinion
53


of occupational prestige. It has long been debated if tbese scores apply to females
as well. I agree with Lockwood that occupational prestige goes with the
occupation not with the gender, in as much as the occupation itself is gender
neutral, such as doctor or accountant. However, the problem remains that some
occupations simply are not gender neutral. This is responsible for some
subjective bias that certain occupations are less prestigious than the equivalent
male counter part. This bias may be evident in the number of women in my
sample who are in the three occupational prestige levels. I did not attempt to
make any adjustments for this.
2.1 am aware that there can be certain problems in the scoring system of
the SEI. It works reasonably well when all scores are used in interval
measurement, but can have some inconsistencies when turned into categories and
used with ordinal methods of measurement, such as I have done in cross
tabulations.
3.1 am also aware that measuring respondents' social class using mothers'
occupational prestige does not account for the occupational prestige of mothers
who are not in the workforce. Although some attempts have been made (Bose,
1973; Treiman and Terrell, 1975) to create a category of "homemaker" and create
an appropriate occupational prestige score, so far no standardized score has been
accepted in the social sciences.
54


4. When creating the dichotomous variables of mothers' and women's
work history, I did not take into account whether or not work was part-time or
full-time. Studies show that women who work part time are less likely to have
high prestige jobs. I am aware that this could make a difference in the
occupational prestige scores of the women and the mothers.
55


CHAPTER 4
DATA ANALYSIS
The first objective of this analysis of measurements for women's social status
is to do simple comparisons of women's and mothers' social class indicators, by using
cross tabulations to discover if mothers' work history, years of education and
occupational prestige have any association to the work history, years of education,
occupational prestige, and subjective class identity of women. If there is a
relationship, then it is important to create linear regression models and explore the
strength of those relationships. However, before we can be certain that mothers'
social class indicators do positively affect women's social position, we need to
understand separately the associations between a woman and the other prominent
people in her life, namely, her father and spouse.
The second objective is to compare fathers' and spouses' years of education
and occupational prestige separately to examine any positive or negative associations
and the strength of the associations to women's occupational prestige and subjective
class identity. If associations are found between a woman's social class indictors and
those of her mother, father and spouse, it is important to analyze the strength of the
social class indicators from the mother, father, and spouse. Therefore, I will compare
56


women's occupational prestige to the years of education and occupational prestige of
mothers, fathers and spouses.
In recent years, women are more inclined to consider their own social class
indicators when measuring their social class. The third objective, then, is to create
linear regression models comparing women's own years of education and
occupational prestige together with mothers', fathers' and spouses' years of education
and occupational prestige to women's subjective class identity. By using linear
regression models, it is possible to compare the strength of each association
independent of the others. However, because we are seeking intergenerational
influences on women's social status, the fourth objective will be to compare women's
occupational prestige and subjective class identity to only mothers' and fathers' years
of education and occupational prestige.
Past studies claim that even if women are giving more strength to their own
social class indictors, they are still primarily measuring their social class position by
their husband's social status indicators. The fifth objective will compare women's
subjective class identity with their own years of education and occupational prestige
and that of their spouses, to see if this is still the norm.
If the traditional method of measuring social status, using male head of
household as the measurement for family class is still valid, then women's social class
indictors of years of education and occupational prestige should not be significant to
57


men's perspective of their own subjective class identity. The sixth objective is to see
if wives are influencing how men measure their own subjective class identity, by first,
comparing men's subjective class identity with their own years of education and
occupational prestige and that of mothers, fathers, and spouses, and then by
comparing men's subjective class identity with their own years of education and
occupational prestige and that of their spouses only.
Some of the tables in the following analysis have been edited to emphasize the
relevant data. Complete tables can be found in Appendix A.
Cross Tabulation Models for Comparing Women and
Their Mothers' Work History. Years of Education,
and Occupational Prestige
By examining the data on female respondents and the data available on their
mothers, several conclusions can be reached about the effect of mothers' work history,
years of education, and occupational prestige on daughters. The division of women
into birth cohorts and then into an early and a late year category gives a more
historically clear picture of the cultural context in which the mothers as well as their
daughters were bom, attended college, and were in the work force. The following
tables show that mothers do have influence over women's occupational prestige and
subjective class identity and that the influence has grown stronger in recent years.
58


Table 4.1
Work History of All Female Respondents and All Mothers* of
Respondents from GSS 1973 and 1998
Women Who Work or Have Worked (Percent saying yes) Mothers Who Worked (Percent saying yes)
All Women 1973 i 46.0% I 48.1%
Number of Respondents ! 347 i ! 331 i
All Women 1998 i 79.5% ! 62.3%
Number of Respondents i 1212 i 923
*Data on mothers work history not available for year 1972
Looking at women's participation in the labor force, in Table 4.1 we see the
increase in women who work or have worked and, the increase in mothers who
worked, for ALL women in the General Social Surveys from 1973 to 1998. As we
can see, the number of women in the labor force increased by 72% between 1973 and
1998. How does the increase in women working compare with the percent of mothers
who worked? The number of mothers who worked increased by nearly 30% from
1973 to 1998. By 1998 over 60% of women had mothers who worked or had worked
at sometime in their lives. These figures closely agree with U. S. Census data, that
show in 1970, 38% of women worked, but by the year, 2000 about 60% of all adult
women were in the labor force. Knowing that there has been an increase in the
number of women in the work force is an important feature of the change in how
women measure their social status.
59


In Table 4.2, the older cohort, age 40-50,1973 through 1978, at 49.6%, had a
1 in 2 chance to be working and to have mothers who worked while they were
growing up.
Table 4.2 Percent of Women Who Work Who Had Mothers Who Worked*
While They Were Growing Up Women 40 to 50 and 30 to 40
1973-1978 and 1991-1998
Women Who Are Working
(Percent saying Yes)
1 1 1973-1978 1 1 1991-1998
Mother Worked Birth Cohort 40-50 1 1 49.6% 1 | 67.7%
Number of Respondents 1 1 1 207 1 1 1 755
Mother Worked Birth Cohort 30-40 l l 67.3% 1 1 1 76%
Number of Respondents 1 334 1 955
Data on mothers work history not available for year 1972
The percentages of women and mothers working or not working are fairly
evenly distributed over the four possibilities (see Appendix Table 4. la). However,
there are significant changes that occur between the birth years of the younger cohort
and the older cohort. We see that, of women age 30-40 in 1973-1978, over 67% of
the women who worked had mothers who also worked. For years 1991-1998, both
birth cohorts show an increase in the number of women who work who had mothers
who worked while they were growing up, ranging from nearly 68% for the women
age 40-50, to 76% for the women age 30-40. In just a few years, the women who
work with mothers who worked while they were growing up increased progressively
from 1 out of 2, to 2 out of 3, to 3 out of 4.
60


The greater numbers of women in the labor force has a parallel effect through
the process of women's increased years of education that would also influence
women's occupational prestige and subjective class identity. As we can see in Table
4.3, for ALL women respondents in 1973 and 1998 in the General Social Survey the
number of women who have at least one year of college increased nearly 125 % from
23.1% to 51.7%. This table shows that for ALL women the number of mothers with
at least one year of college also increased by 125%, from 11.8% to 26.9%.
Table 4.3 Years of Education of AH Women and All Mothers of Respondents
from GSS 1973 and 1998
All Women 1973 All Women 1998
Women Who Completed At Least One Year of College
(Percent saying yes) 23.1 51.7
Number of Respondents 186 824
Mothers Who Completed At Least One Year of College
(Percent saying yes) 11.8% 26.9%
Number of Respondents 72 363
This is understandable in the historical context of the decades when the
mothers would have attended college. The mothers of the older birth cohort would
have attended college from about 1910 to 1930, while the younger mothers of the
younger cohort would have attended college between approximately 1940 and 1960.
U. S. Census data show there was a 150% increase from 1940 to 1970 in the number
of American women 25 years old or older who have at least some college education,
and between 1970 and 2000, the increase was 329% (U. S. Census).
61


Whether or not a woman works or has educational opportunities is
undoubtedly a response to issues other than whether or not her mother worked. One
possible factor is that children of working mothers may tend to be more independent,
which could have the effect that a daughter was more likely to work as an adult.
Other influences on whether a woman works or not would be economic necessity,
being a single parent, and, of course, the time-phased job mobility acquired by the
increased years of higher education. That women, over time, increased their years of
education could demonstrate that they are applying new opportunities to their work
experience. The number of women and mothers who are in the work force has
increased rapidly in the last half of the twentieth century.
Whatever the reason that mothers and daughters are obtaining more years of
education and participating in the labor force, they are establishing occupational
prestige for themselves. Because education and occupation function as indicators of
social status, the increase in years of education and occupational prestige women and
their mothers are making, logically should be making a difference in their own social
status. It would seem predictable that mothers' increased years of education would
have an affect, over time, on the occupational prestige of women.
If we look at the highlighted figures in Tables 4.4, we see that of the women
who had mothers who did not complete high school, 76.5% of the 40-50 year olds and
67.9% of the 30-40 year olds have occupations that are in the low prestige category.
62


The mothers who have at least one year of college have few daughters who are in the
low prestige category, only 4.6% and 6.2% respectively.
Table 4.4 Effects of Mothers' Years of Education on Occupational
Prestige Women 40 to 50 and 30 to 40 1972-1978
Occupational Prestige Score of Women
Women Age 40-50 Women Age 30-40
Mothers Years of Low Middle High Prestige j Prestige [Prestige] Low Middle j High j PrestigejPrestigejPrestigej
Education 10-32 | 37-62 63-89 1 Total 10-32 1 33-62 | 63-89 Total
Did Not Complete High School r r t 1 1 1 1 1 1 1 1 1 1 1 1 76.5% j 56.7% | 34.6% 165.4% n ft 1 1 1 1 1 1 1 1 1 67.9% 42.5% 32.1% 153.9% i i i
High School Graduate i i i i i i i i i 18.9% | 27.0% | 30.8% |23.3% i i i i i i i i i i i i 25.9% | 40.6% | 28.6% |33.5% i i i
At Least One Year of College i i i i i i i i i 4.6% j 16.3% | 34.6% '[11.4% i i i i i i i i i i i i 6.2% J 16.9% i 39.3% Jl2.6% i i i
Total Percent 100% I 100% | 100% | 100% i i i 100% j 100% I 100% |ioo%
Number of Respondents 349 356 26 731 452 503 28 1524
In Table 4.4, looking at the highest occupational prestige category for women
40-50 years of age, we see that 34.6% have mothers whose years of schooling
includes at least one year of college, and of the 30-40 year olds women 39.3% have
mothers who have some college education. One thing of note about Table 4.4 is that
the women with high occupational prestige are fairly evenly distributed regardless of
the years of education of their mothers. I believe this consistency parallels the
educational and occupational opportunities available to women in recent decades that
were not available to the mothers.
63


For both birth cohorts in Table 4.4,1972-1978, only about 12% of the mothers
had at least one year of college education. Census figures support this data. In 1940,
the year on average, the mothers would have been finishing four years of college, less
than 4% of women had at least four years of university education. In 1970, 8% of
women 25 years old or older had at least four years of college, and data from the most
recent census of 2000, show that the number of women with at least four years of
college is over 23% of the general population (U. S. Census).
Opportunities for women increased dramatically between 1970 and today. If
we look at Table 4.5 showing women by birth cohort in 1991-1998, we can see that
the differences in mothers' years of education compared to daughters' occupational
prestige gradually ameliorate from the 1970s to the 1990s.
In Table 4.5, for the youngest birth cohort, women age 30-40 in the years
1991-1998, about 34% of women who had mothers that did not finish high school
remain in the lowest occupational prestige categoiy. This is about half the number as
shown in Table 4.4 for the 1970s. In Table 4.4 and 4.5, of the women who had
mothers who finished at least one year of college, the number of women 40-50 in the
highest prestige category increased to 37.1% from 34.6% and for women 30-40 from
39.3% to 42.5%. For women age 40-50 in 1991-1998, the number of mothers with
some college education doubled to 23%, and for the younger cohort, age 30-40, it
nearly tripled from 12.6% to 30.1%.
64


Table 4.5
Effects of Mothers' Years of Education on Occupational
Prestige Women 40 to 50 and 30 to 40 1991-1998
Occupational Prestige Score of Women
Women Age 40-50 Women Age 30-40
Mothers Years of Low i Middle j High j PrestigejPrestige| Prestige j Low j Middle! High j Prestige jPrestigej Prestige j
Education 10-32 37-62 63-89 Total 10-32 33-62 I 63-89 Total
Did Not Complete High School 1 1 1 1 1 1 1 1 1 1 1 1 49.0% | 31.9% | 24.9% | 35.9% 1 1 1 1 1 1 1 1 1 1 1 1 34.3% | 21.7% | 17.1% | 25.3% 1 1 1
High School Graduate 1 1 1 1 1 1 1 1 1 38.7% j 44.1% 38.0% | 41.4% i i i 1 1 1 1 1 1 1 1 1 43.9% | 46.3% | 40.4% | 44.6% i i i
At Least One Year of College i i i i i i 12.4% i 24.0% i 37.1% | 22.7% i i i i i i i i i i i i 21.8% 32.0% | 42.5% i 30.1% i i i
Total Percent i i i 100% S 100% I 100% S 100% 100% I 100% I 100% |l00%
Number of Respondents 388 653 221 1262 522 774 228 1524
As Table 4.5 shows, by the 1990s, the members of the younger birth cohort are
more evenly distributed in the prestige categories and the mothers have more years of
education. Both are significantly augmented by the increase in high school graduation
levels of mothers. If we look back at Table 4.4, we see that in the 1970s only about
23% of mothers of the older women had a high school diploma, by the 1990s in Table
4.5, nearly 45% of the mothers of the younger birth cohort had graduated from high
school.
I think it is safe to say that in the last thirty years, mothers with more
education have had a positive effect on the amount of education that daughters
obtained. In Tables 4.4 and 4.5, we find a direct relationship between mothers' years
of education and women's occupational prestige. With better education, women are
65


able to obtain higher occupational prestige, and this would have a decisive affect on
how their social status is measured. The more education the mother has the more
likely her daughter is to be in the highest occupational prestige group. Mothers'
increased education has to affect daughters' social status. This seems to be such
convincing proof of the effectiveness of mothers' educational attainment on daughters'
socio-economic success, that one wonders that there shouldn't be an ad campaign
encouraging young women to go to college if only for the sake of their future
daughters.
An additional effect on women's occupational prestige besides mothers' years
of education is the influence that mothers' occupational prestige has on women's
occupational prestige. It should be noted that in Table 4.6 and any other tables using
mothers' occupational prestige, the data are from GSS years 1994, 1996, and 1998.
Asking respondents mothers' occupation and measuring mothers' occupational
prestige score has been a part of the General Social Survey questionnaire only since
1994. Even in this limited amount of time, however, the data show that mothers'
occupational prestige is an influencing characteristic affecting women's occupational
prestige.
Particularly obvious in Table 4.6 is that the majority of women who have low
prestige occupations have mothers who also had low prestige occupations, over 72%
of women 40 to 50 years old and 56% of the women 30-40. Conversely, of the
66


women 40-50 with low prestige jobs, only 5.6% have mothers with high prestige jobs;
and of the women 30-40, with low prestige jobs, only 7.1% have mothers with high
prestige jobs.
Table 4.6 Affects of Mothers' Occupational Prestige on Occupational
Prestige Women 40 to 50 and 30 to 40 1994-1998
Occupational Prestige Score of Mothers
Low Occupational Middle Occupational High Occupational
Prestige 10-36 Prestige 37-62 Prestige 63-89
Occupational Prestige Women Women Women Women Women Women
Score of Women 40-50 30-40 40-50 30-40 40-50 30-40
Low Occupational i r r
Prestige 10-32 113% 55.7% 22.1% 37.1% 5.6% 7.1%
Middle Occupational
Prestige 37-62 49.9% 41.4% 38.6% 47.1% 11.5% 11.4%
High Occupational
Prestige 63-89 28.4% 32.2% 43.1% 47.5% 28.4% 20.3%
Total Percent 24.6% 45% 34.3% 43.8% 12.4% 11.2%
Number of Respondents 339 368 218 358 79 92
As explained by child socialization processes, children who have mothers who
are high achievers tend to be high achievers themselves. Higher achievement for
daughters is no doubt also affected by greater acceptance of women's contemporary
gender roles. Before the case can be positively stated for inclusion of data about
mothers into measurement of social stratification, it is important to understand how
mothers' influence compares to the influence of women's fathers and husbands.
67


Separate Regression Models of Effects of Mothers'. Fathers',
and Spouses' Years of Education and Occupational Prestige
on Women's Occupational Prestige and Subjective Class Identity
While it seems undeniable that mothers influence the years of education and
occupational prestige of daughters and thusly women's social prestige, it is likely that
the effect of fathers and spouses influence is also a factor in measuring women's
social status.
In Tables 4.7 through 4.12,1 regress separately the dependent variables
women's occupational prestige and subjective class identity against mothers',
fathers', and spouses' years of education and occupational prestige to test the
strength and direction of effects.
Table 4.7 Correlation-Regression Analysis for the Relationship of Mothers'
Years of Education and Occupational Prestige to the Occupational
Prestige Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
Independent Standard j j ized ! Coefficient! Correlations 1 1 1 1 Standard j j ized j Correlations
Variables s j Signifi j Zero Partial Coefficients j Signifi [Zero Partial
(Constant) (Beta) cance jOrder (Beta) j cance (Order
Mothers' Years of Education i i i i i i .149 | .002 j .262 | .128 i i i i i i .107 | .011 | .196 | .092
Mothers' Occupational Prestige i i i i i i i i i i i i i i i .197 .000 .283 .168 i i i i i i i i i i i i i i i i i i .163 .000 .221 .139 i i i
Multiple R R* i i i .308 i ! i i i .239 i !
.095 1 1 .057 | | |
Regression coefficient significant at p>.05, two tailed test
68


Although subjective class identity is an ordinally measured variable, in all the
following tables, it has been handled as an intervally measured variable.
We see in Table 4.7 that according to the Beta coefficients, mothers' years
of education and occupational prestige by themselves are both significant in
influencing women's occupational prestige for both birth cohorts.
In Table 4.8, when women's subjective class identity is regressed on
mothers' years of education and occupational prestige, although the amount of
effect from the beta weights is similar, it is mothers' years of education that is
significant to the older birth cohort, and mothers' occupational prestige that is
significant to the younger birth cohort.
Table 4.8 Correlation-Regression Analysis for the Relationship of Mothers'
Years of Education and Occupational Prestige to the Subjective Class
Identity Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
Standard 1 1 1 1 1 1 Standard 1 1 1 1 1 1 1 1
Independent ized i i Correlations ized i I Correlations
Variables Coefficients j Signifi j Zero Partial Coefficients) Signifi{ Zero Partial
(Constant) (Beta) ! cance 1 Order (Beta) 1 cance Order
Mothers' Years of Education .185 i J O o o N) U) L/i .037 i 1 i i i i | .381 j .141 | .031
Mothers' Occupational Prestige .086 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 .072 .192 .071 .188 i i i i i i i i i i i i i i i i .000 i .208 J .158
Multiple R .245 i i i .210 i i i
R2 .060 i i i .044 i i i
Regression coefficient significant at p>.05, two tailed test.
69


In Table 4.9, comparing women's occupational prestige with their fathers'
indicators for women in both age cohorts, it is fathers' years of education that is
significant. For the younger cohort fathers' occupational prestige is also significant.
Table 4.9 Correlation-Regression Analysis for the Relationship of Fathers'
Years of Education and Occupational Prestige to Occupational
Prestige Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
1 1 1 1 Standard ! Standard 1 1 1 1 1 1 1 1
Independent ized j | Correlations ized j j Correlations
Variables Coefficients iSignifi! Zero Partial Coefficients ISignifi | Zero Partial
(Constant) (Beta) cance | Order (Beta) j cance j Order
Fathers' Years of 1 1 1 I 1 1 1 1 1
Education .208 S .000 i .242 i i i i .177 .173 i .000 i .251 i .148 1 1 1
Fathers' i i i i i i i i i 1 I 1 1 1 1 1 1 1
Occupational i i i i i i 1 1 1 1 1 1
Prestige .063 | .130 j .176 | .054 .140 j .000 | .237 | .120
Multiple R .247 1 1 1 .277 1 1 1
R2 .061 1 1 1 .077 1 1 1
Regression coefficient significant at p>.05, two tailed test
Table 4.10 Correlation-Regression Analysis for the Relationship of Fathers'
Years of Education and Occupational Prestige to Subjective Class
Identity Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
Standard 1 1 1 1 1 1 1 1 Standard 1 1 1 1 1 1 1 1
Independent ized j j Correlations ized j j Correlations
Variables Coefficients ISignifi| Zero Partial Coefficients | Signifi J Zero Partial
(Constant) (Beta) I cance I Order (Beta) I cance 1 Order
Fathers' Years of 1 1 I 1 1 1 1 1 1 1 1 1
Education .259 1 .000 j .288 | | j .222 | .205 I .000 I .237 | I j .173 1
Fathers' 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Occupational 1 1 1 1 1 1 1 1 1 1 1 1
Prestige .055 I .167 I .195 I .049 .057 1 .144 I .172 I .049
Multiple R .292 1 1 1 .242 1 1 1
R2 .085 1 1 1 .059 1 1 1
Regression coefficient significant at p>.05, two tailed test.
70


In Table 4.10, fathers' years of education has the strongest effect. It is
significant to the subjective class identity of both birth cohorts, and the Beta for
fathers' years of education for the older women at .259 is the strongest influence so
far.
The R-squared in Tables 4.7 through 4.10 show that fathers' and mothers'
indicators have similar strength and women are deriving only a modest amount of
their social status from parents individually. This tells us only a small part of the
story; we know from previous studies that husbands' social class indictors also have
an effect on the social class of their wives.
Tables 4.11 and 4.12 compare women and their spouses.
Table 4.11 Correlation-Regression Analysis for the Relationship of Spouses'
Years of Education and Occupational Prestige to Occupational
Prestige Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
Standard f 1 1 1 1 1 1 1 Standard 1 1 1 1 1 1 1 1
Independent ized i i Correlations ized i i Correlations
Variables Coefficients jSignifij Zero Partial Coefficients j Signifi ] Zero Partial
(Constant) (Beta) ! cance Order (Beta) ! cance Order
Spouses' Years i i i i i i i i i i i i
of Education .270 I .000 | .378 | .236 .206 I .000 | .328 | 1 1 1 .176
Spouses' 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Occupational 1 1 1 1 1 1 1 1 1 1 1 1
Prestige .188 i .000 .343 i i i .167 1 .207 ! .000 | .328 i i i .177
Multiple R .408 i i i i 1 1 .368 i i i i i i
R2 .167 i i i 1 i .135 i i i
Regression coefficient significant at p>.05, two tailed test.
71


Table 4.12
Correlation-Regression Analysis for the Relationship of Spouses'
Years of Education and Occupational Prestige to Subjective Class
Identity Women 40 to 50 and 30 to 40 1994-1998
Women 40-50 Women 30-40
Independent i i Standard | ized 1 1 1 1 | Correlations Standard ized 1 1 1 1 1 1 1 1 j j Correlations
Variables Coefficients j SignifiJ Zero Partial Coefficients j SignifI J Zero Partial
(Constant) (Beta) i cance Order (Beta) ! cance Order
Spouses' Years of 1 1 1 1 1 1 1 1 1 1
Education .360 | 1 .000 | .458 | .317 1 .355 1 .000 I .428 S .304 1 1 1
Spouses' 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Occupational 1 1 1 1 1 1 1 1 1 1
Prestige .170 i .000 .378 ! .156 i .124 ! .003 .333 .111 i i i
Multiple R F? .427 | i i .439 i i i i i i
.229 ! i .193 i i i
Regression coefficient significant at p>.05, two tailed test
In both Table 4.11 and 4.12, spouses' years of education and occupational
prestige are significant in influencing women's occupational prestige and subjective
class identity for both birth cohorts.
The Beta weights suggest that the strongest individual influence on women's
class identity comes from spouses' years of education rather than from mothers or
fathers indictors. These separate regressions of mothers, fathers', and spouses' years
of education and occupational prestige, while significant have only moderate
influence. For both birth cohorts it would seem that women are not deriving their
social class position from their husbands, as strongly as previous studies would have
us believe; and the younger women are slightly less affected by their spouses'
indicators than the older women.
72


Combined Regression Models of Effects of Mothers.
Fathers', and Spouses' Years of Education and Occupational
Prestige on Women's Occupational Prestige
and Subjective Class Identity
In this analysis, it is important to create an all inclusive model of the
independent variables, of mothers', fathers' and spouses' years of education and
occupational prestige, and the dependent variables, of women's' occupational prestige
and subjective class identity, to test the strength of parental and spousal indicators
when regressed against each other.
In Table 4.13, for the older birth cohort it is mothers' occupational prestige and
spouses' years of education that are significant to the occupational prestige of the
older women.
Table 4.13 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers' and Spouses' Years of Education and Occupational Prestige
to Occupational Prestige Women 40 to 50 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education .111 .149 .292 .091
Mothers' Occupational Prestige .183 .013 .303 .156
Fathers' Years of Education -.034 .638 .204 -.030
Fathers' Occupational Prestige .038 .565 .187 .037
Spouses' Years of Education .290 .000 .373 .252
Spouses' Occupational Prestige .043 .539 .252 .039
Multiple R .455
R2 .207
Regression coefficient significant at p>.05, two tailed test
73


Fathers' indictors have no significance, and in fact, as shown by Beta, fathers' years of
education appears to have a negative impact on women's occupational prestige. The
strongest effect on women's occupational prestige is Beta at .290 from spouses' years
of education.
For women in the younger cohort, in Table 4.14, it is fathers' and spouses'
occupational prestige that are significant to the measurement of women's occupational
prestige. Of the beta coefficients, at .172, variation in spouses' occupational prestige
has the strongest effect on changing women's occupational prestige.
Table 4.14 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', and Spouses' Years of Education and Occupational Prestige
to Occupational Prestige Women 30 to 40 1994-1998
Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education .073 .278 .234 .062
Mothers' Occupational Prestige .031 .638 .225 .027
Fathers' Years of Education .080 .246 .288 .066
Fathers' Occupational Prestige .143 .025 .299 .128
Spouses' Years of Education .105 .115 .301 .090
Spouses' Occupational Prestige .172 .008 .308 .152
Multiple R .418
R2 .174
Regression coefficient significant at p>.05, two tailed test
These tables show that for the older women, it is mothers' that affect women's
occupational prestige and for the younger women it is fathers who have an effect, but
in both cases it is spouses who have the most effect.
74


To continue to explore the intergenerational influences on women's social
status, I temporarily discard the data on husbands. This gives a better understanding
if data on mothers is becoming significant and should possibly be included in the
indicators measuring social status. Tables 4.15 and 4.16 present the results of
women's subjective class identity regressed against only mothers' and fathers' years of
education and occupational prestige.
In Table 4.15 for women 40-50 years of age, of the parental achievements that
are significant to women's occupational prestige it is mothers' years of education and
occupational prestige that are important not fathers'. Beta coefficients show that
variations in mothers' years of education and occupational prestige affect the
occupational prestige of daughters.
Table 4.15 Correlation-Regression Analysis for the Relationship of Mothers'
and Fathers' Years of Education and Occupational Prestige to
Occupational Prestige Women 40 to 50 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) 1 1 1 1 1 j Significance Correlations Zero Partial Order
Mothers' Years of Education .119 j .042 .250 1 .094
Mothers' Occupational Prestige .184 j .001 1 .276 1 1 1 .149
Fathers' Years of Education .016 i .793 .192 1 1 1 .012
Fathers' Occupational Prestige .058 ! ^ .274 i .166 1 l 1 .049
Multiple R .305 i i i 1 1 1
R2 .093 i i 1 1
Regression coefficient significant at p>.05, two tailed test
75


For women 30-40, Table 4.16, it is mothers' occupational prestige, fathers'
years of education, and fathers' occupational prestige that are all significant for
measuring women's occupational prestige, but these are not as significant as
mothers' indicators for the older women, as shown in Table 4.15, and none of the
Beta weights have as strong an influence as that for mothers' occupational
prestige.
Table 4.16 Correlation-Regression Analysis for the Relationship of Mothers'
and Fathers' Years of Education and Occupational Prestige to
Occupational Prestige Women 30 to 40 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance j Correlations Zero Partial i Order
Mothers' Years of Education .025 .638 j .196 .020
Mothers' Occupational Prestige .105 .035 I .209 i .090
Fathers' Years of Education .130 .015 i .253 .103
Fathers' Occupational Prestige .129 .010 j .247 i .110
Multiple R .303 i i i
R2 .092 i
Regression coefficient significant at p>.05, two tailed test.
Obviously there are other factors influencing women's occupational prestige. I
would suspect that because there are more women in the labor force today, women are
apt to have more interest in parental occupational prestige as a measure of their social
class. While parents are having some affect on women's occupational prestige, are
they also affecting women's subjective class identity? Tables 4.17 and 4.18 explore
76


women's subjective class identity in relation to parents' years of education and
occupational prestige.
Table 4.17 shows that both mothers' and fathers' years of education are
significant to a woman's subjective class identity with fathers years of education
showing the strongest direct relationship.
Table 4.17 Correlation-Regression Analysis for the Relationship of Mothers'
and Fathers' Years of Education and Occupational Prestige to
Subjective Class Identity Women 40 to 50 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education .113 .050 .268 ! .090
Mothers' Occupational Prestige .070 .191 .227 | .060 i
Fathers' Years of Education .191 .001 .300 ! .149
Fathers' Occupational Prestige .028 .586 .192 i .025 i
Multiple R .330 i i
R2 .109 i
Regression coefficient significant at p>.05, two tailed test.
Table 4.18 Correlation-Regression Analysis for the Relationship of Mothers'
and Fathers' Years of Education and Occupational Prestige to Subjective
Class Identity Women 30 to 40 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education -.074 .166 .115 -.059
Mothers' Occupational
Prestige .136 .007 .181 .115
Fathers' Years of Education .184 .001 .226 .142
Fathers' Occupational Prestige .054 .291 .178 .045
Multiple R .259
R2 .067
Regression coefficient significant at p>.05, two tailed test.
77


For women 30-40, in Table 4.18, it is mothers' occupational prestige and
fathers' years of education at that are significant to women's subjective class
identity. The change from mothers' years of education to mothers' occupational
prestige could possibly be explained as an effect of the increased numbers of
career oriented women and mothers in the labor force.
Combined Regression Models of Effects of Women's Years
of Education and Occupational Prestige and Mothers'. Fathers',
and Spouses' Years of Education and Occupational Prestige
on Women's Subjective Class Identity
As we saw in the previous tables, the two age cohorts do not entirely agree
about the effects of parental influence on their occupational prestige or subjective
class identity, but when we compare women's subjective class identity to her own
occupational prestige and that of mothers', fathers', spouses', the older and the
younger birth cohorts are of the same mind about their subjective class identity.
In Table 4.19, for women 40-50, their own occupational prestige and that
of their mother and spouse are significant to women's subjective class identity.
We see that fathers' occupational prestige is not significant. Spouses'
occupational prestige has the strongest effect on women's subjective class
identity, but interestingly, the beta coefficient of mothers' occupational prestige at
78


.183, has more influence on women's occupational prestige than women's own
occupational prestige at .117, in the selection of subjective class identity.
Table 4.19 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', Spouses' and Woman's Occupational Prestige to Subjective
Class Identity Women 40 to 50 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) 1 1 1 j Correlations Zero Partial Significance! Order
Mothers' Occupational 1 1 1 1
Prestige .183 .002 | .267 | .185
Fathers' Occupational 1 1 1 1
Prestige .050 .399 | .216 | .051
Spouses' Occupational 1 1 1 1
Prestige .339 .000 .396 ! .344
Woman's Occupational 1 1 1 1
Prestige .117 .045 j .267 1 ! .122 i
Multiple R .475 1 1 | i i i
R2 .225 1 i j
Regression coefficient significant at p>.05, two tailed test
In Table 4.20, for women 30-40 years of age, again, it is their own
occupational prestige and that of mothers and spouses that are significant to
women's subjective class identity. Again, fathers' occupational prestige is not
significant. While spouses' influence is still moderately strong at Beta .293, it
should be noted that it has decreased and women's own occupational prestige at
Beta .187 has increased causing it have more effect than it did for the older
women as shown in Table 4.19.
79


Table 4.20
Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', Spouses' and Woman's Occupational Prestige to Subjective
Class Identity Women 30 to 40 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Occupational i i
Prestige .113 .037 .229 .113
Fathers' Occupational 1 1
Prestige .012 .830 .182 .012
Spouses' Occupational 1 1
Prestige .293 .000 .378 | .292
Woman's Occupational 1 1
Prestige .187 .000 .303 j .189 1
Multiple R .442 1 1 1
R2 .196 1
Regression coefficient significant at p>.05, two tailed test.
The previous tables partially explain women's occupational prestige and
subjective class position. This demonstrates that along with their own
occupational prestige and that of their husband, for women, a mothers'
occupational prestige is a factor in explaining how women determine their class
position. The small R-squared tells us there are obviously other influencing
factors affecting women's social class position, not least of which are other of her
own social status indictors. We know that subjective class association is an
individual's own perception of where they are in the status hierarchy and is a
cognitive creation, so how does women's own years of education and
occupational prestige affect subjective class identity along with mothers', fathers'
and spouses' years of education and occupational prestige?
80


In Tables 4.21 and 4.22, women's own years of education and
occupational prestige and mothers, fathers and spouses years of education and
occupational prestige are compared to womens subjective class identity. As we
see in Table 4.21, when a 40-50 year old woman's subjective class identity is
compared to her own years of education and occupational prestige and those of
her mother, father, and spouse, it is mothers' years of education and spouses' years
of education and occupational prestige that are significant factors affecting her
subjective class identity.
Table 4.21 Correlation-Regression Analysis for the Relationship of Mothers,
Fathers, and Spouses', and Women's Years of Education and
Occupational Prestige to Subjective Class Identity Women 40 to 50
1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education .170 .018 .364 .150
Mothers' Occupational Prestige .017 .808 .267 .015
Fathers' Years of Education .108 .110 .329 .102
Fathers' Occupational Prestige -.037 .545 .204 -.039
Spouses' Years of Education .217 .002 .461 .191
Spouses' Occupational Prestige .184 .005 .412 .177
Women's Years of Education .128 .083 .423 .110
Women's Occupational Prestige .020 .758 .292 .020
Multiple R .580
R2 .336
Regression coefficient significant at p>.05, two tailed test.
81


These eight indicators explain nearly 34% of women's subjective class
identity in spite of the fact that fathers' years of education and occupational
prestige continue to not be significant.
It is important to point out that for this older birth cohort, their own
indictors are not significant. This is possibly a telling example of the culturally
socialized subjectivity that the older women used to measure their class identity.
For the younger birth cohort in Table 4.22, we see that this has changed.
Table 4.22 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', Spouses', and Women's Years of Education and Occupational
Prestige to Subjective Class Identity Women 30 to 40 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education -.033 .615 .136 -.029
Mothers' Occupational Prestige .090 .145 .207 .084
Fathers' Years of Education -.015 .820 .196 -.013
Fathers' Occupational Prestige -.049 .423 .162 -.046
Spouses' Years of Education .326 .000 .464 .261
Spouses' Occupational Prestige .143 .020 .386 .133
Women's Years of Education .036 .615 .346 .029
Women's Occupational Prestige .144 .013 .298 .142
Multiple R .515
R2 .265
Regression coefficient significant at p>.05, two tailed test.
In Table 4.22, for the younger cohort of women, it is not only spouses'
years of education and occupational prestige that are significant in measuring
women's subjective class position, but also these younger women are taking into
82


account their own occupational prestige when determining their subjective class
identity. For these younger women, their own occupational prestige is significant
at .013 in their selection of their class position. While mothers' years of education
and occupational prestige are not significant here, previous comparisons show
that mothers' indicators do have an effect on women's own indicators. As this
study shows in previous tables, women's years of education and occupational
prestige are influenced by the years of education and occupational prestige of
mothers.
Regression Models of Effects of Women's Years of Education
and Occupational Prestige and Spouses Years of Education
and Occupational Prestige on Women's Subjective Class Identity
If women's own class indicators are regressed only against those of
spouses, do spouses' indicators remain as strong? The traditional method for
measuring women's social class has been to use only data on male head of
household. Studies using this perspective maintain that husbands' social status
has the largest impact on women's social status and husbands' social class as
measured by his socio-economic index is the best indicator of women's social
class. This point of view maintains that even if women are giving more strength
to their own social class indictors, they are still primarily "borrowing" their social
class position using their husbands' social status indicators. (Goldthorpe 1983,
83


Sorensen 1994, Baxter 1994, Simpson et. al 1994). However, as this study has
shown so far, the younger birth cohort of women 30-40, are beginning to use the
"sharing" model and "independent" model to measure their social class using their
own individual indicators. (Davis and Robinson 1988)
In Tables 4.23 and 4.24, where women's years of education and
occupational prestige are regressed against spouses' years of education and
occupational prestige, we see that this effect continues. In Table 4.23 for the
older birth cohort, women 40-50 in 1972 to 1978, it is only spouses' years of
education and occupational prestige that are significant to subjective class
identity.
Table 4.23 Correlation-Regression Analysis for the Relationship of Women's
and Spouses' Years of Education and Occupational Prestige to
Subjective Class Identity Women 40 to 50 1972-1978
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Women's Years of Education -.009 .864 .231 -.007
Women's Occupational Prestige .073 .131 .239 .062
Spouses' Years of Education .151 .004 .336 .119
Spouses' Occupational Prestige .264 .000 .377 .223
Multiple R .407
R2 .166
Regression coefficient significant at p>.05, two tailed test.
However, as we progress through the year groupings, from the younger
women in 1972-1978, Table 4.24, to the older women in 1991-1998, Table 4.25,
to the younger women in 1991-1998, Table 4.26, we see that women begin to
84


measure their subjective class identity by their own years of education and
occupational prestige. In Table 4.24, when women's subjective class identity is
regressed against her own social status indicators and those of spouses, we see
that spouses indictors are significant and still having the strongest effect on
women's class identity, but women's years of education has become significant.
Though the effect is small at a Beta coefficient of .100, it nevertheless shows
women's new awareness to their own achievements when measuring their class
identity. As data show, these are achievements that have a relationship to the
achievements of their mothers.
Table 4.24 Correlation-Regression Analysis for the Relationship of Women's
and Spouses' Years of Education and Occupational Prestige to
Subjective Class Identity Women 30 to 40 1972-1978
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Women's Years of Education .100 .021 .335 .081
Women's Occupational Prestige .041 .302 .267 .036
Spouses' Years of Education .241 .000 .412 .187
Spouses' Occupational Prestige .153 .000 .362 .131
Multiple R .446
R2 .199
Regression coefficient significant at p>.05, two tailed test.
By the years 1991-1998, Tables 4.25 and 4.26, for both the older and
younger women, their own years of education are significant and continue to
affect their subjective class identity. In Table 4.25, spouses' indicators are also
85


significant, but women's years of education is significant and the beta coefficient
has increased to .146 from .100.
Table 4.25 Correlation-Regression Analysis for the Relationship of Women's
and Spouses Years of Education and Occupational Prestige to
Subjective Class Identity Women 40 to 50 1991-1998
Independent Variable (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Women's Years of Education .146 .001 .381 .123
Women's Occupational Prestige .054 .170 .291 .050
Spouses' Years of Education .231 .000 .436 .195
Spouses' Occupational Prestige .185 .000 .392 .171
Multiple R .495
R2 .245
Regression coefficient significant at p>.05, two tailed test
In Table 4.26, showing the latest year grouping, 1991-1998, and the
youngest birth cohort, 30-40, both women's years of education and occupational
prestige have become significant to the women's class identity.
Table 4.26 Correlation-Regression Analysis for the Relationship of Women's
and Spouses' Years of Education and Occupational Prestige to
Subjective Class Identity Women 30 to 40 1991-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Women's Years of Education .148 .000 .380 .123
Women's Occupational Prestige .123 .000 .318 .114
Spouses' Years of Education .210 .000 .401 .176
Spouses' Occupational Prestige .121 .001 .343 .110
Multiple R .470
R2 .221
Regression coefficient significant at p>.05, two tailed test.
86


When the Beta weights in Tables 4.25 and 4.26 are compared, we see that
spouses' years of education and occupational prestige, while still significant are
having a diminishing effect, as women's own years of education are having an
increasing effect.
Regression Models Comparing the Combined Effects of Men's
Years of Education and Occupational Prestige and the Years
of Education and Occupational Prestige of Mothers, Fathers,
and Spouses on Men's Subjective Class Identity
To have parental and spousal social class characteristics included in the
measurement of social stratification, it is important that these characteristics be
meaningful in their influence on both males and females; and before we can
conclusively assume that mothers' social class indicators of years of education and
occupational prestige are important factors in measuring women's social status,
we need to look at how mothers', fathers' and spouses' social class characteristics
influence males. To explore these issues, in the following tables, I replicate
Tables 4.23 through 4.26, this time using data on men.
Because conventional social class measurement uses male head of household to
determine family social class, I look briefly at, 1) the affect that men's years of
education and occupational prestige as well as the years of education and
occupational prestige of mothers, fathers, and spouses have on men's subjective
class identity; and 2) the effect that men's and spouses' years of education and
87


occupational prestige alone have on men's subjective class identity. Again, we
understand subjective class identity to be a self-orienting perspective of individual
awareness of where one fits into the hierarchy of social position. When assessing
family effects on class, studies continually maintain that men are primarily
influenced by their fathers' and their own social status indicators.
Tables 4.27 through 4.32 show that in recent years, this is no longer
entirely true. In Table 4.27, for the older birth cohort of men age 40-50, it is
men's years of education alone that is significant to men's subjective class
identity, with fathers' years of education just outside significance at .054. These
older men are defining their social class by their own occupation with little credit
to the contributions of their mothers, fathers, or spouses.
Table 4.27 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', Spouses', and Mens Years of Education and Occupational
Prestige to Subjective Class Identity Men 40 to 50 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance { i i i i Correlations Zero Partial Order
Mothers' Years of Education -.102 .204 1 1 .122 ! -.085
Mothers' Occupational Prestige -.072 .324 1 1 1 1 .098 | -.066 i
Fathers' Years of Education .161 .054 1 1 1 .266 I .129
Fathers' Occupational Prestige .102 .175 1 1 1 .256 j .091 i
Spouses' Years of Education -.132 .076 1 1 1 .182 | -.119
Spouses' Occupational Prestige .060 .358 1 1 1 .122 | .062 i
Men's Years of Education .404 .000 1 1 1 .460 | .312
Men's Occupational Prestige .118 .113 1 1 .371 ! .106
Multiple r .512 1 1
R2 .262 1 1
Regression coefficient significant at p>.05, two tailed test
88


What is interesting in Table 4.27 is that the older men attribute their class
identity only to their own indicators, but as we see in Table 4.28, the younger men
attribute their class identity to fathers and spouses.
In Table 4.28, for the younger birth cohort of men, age 30-40, the fathers'
years of education has become significant to men's subjective class identity, and
spouses' occupational prestige is now significant. Curiously, men's own
indicators are no longer significant in determining the men's subjective class
identity. As shown by the Beta weights, wives' occupational prestige
contributions the second largest influence to men's subjective class identity.
Table 4.28 Correlation-Regression Analysis for the Relationship of Mothers',
Fathers', Spouses', and Men's Years of Education and Occupational
Prestige to Subjective Class Identity Men 30 to 40 1994-1998
Independent Variables (Constant) Standardized Coefficients (Beta) Significance Correlations Zero Partial Order
Mothers' Years of Education -.082 n .279 .190 -.067
Mothers' Occupational Prestige .005 .936 .153 .005
Fathers' Years of Education .227 .005 .339 .173
Fathers' Occupational Prestige -.010 .883 .214 -.009
Spouses' Years of Education .038 .614 .318 .031
Spouses' Occupational Prestige .199 .003 .311 .185
Men's Years of Education .142 .080 .359 .109
Men's Occupational Prestige .094 .190 .318 .081
Multiple R .463
R2 .214
Regression coefficient significant at p>.05, two tailed test.
89


Full Text

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WOMEN AND SOCIAL STRATIFICATION: THE INFLUENCE OF MOTHERS ON WOMEN'S SOCIAL CLASS by Meredith Greenfield B. A., University of Colorado at Denver, 1999 A thesis submitted to the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Master of Arts Sociology 2002

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This thesis for the Master of Arts Sociology degree by Meredith Greenfield has been approved by

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Greenfield, Meredith (M. A, Sociology) Women and Social Stratification: The Influence of Mothers on Women's Social Class Thesis directed by Professor Richard Holmes Anderson ABSTRACT The continuing use of the conventional method for measuring social class, using the family as the unit of measurement and only data on the male head-ofhousehold, fails to resolve the issue of the Independent social position of women. Women's growing autonomous social class identity is because of recent important cultural and economic changes that affect their social stratification, such as educational attainment, occupational prestige and changing demographics of the family unit. Using intergenerational information from family of origin could provide the indicators of social status, needed as indiVidual class position becomes more independent of the family unit. This issue of intergenerational influences on social class is explored by using data from the General Social Survey 1972 through 1998. The indicators used as independent' variables are mothers' work history, years of education, and occupational prestige. Women's work history, years of education, occupational p-restige, and subjective class identity are the dependent variables. The results of this study show that after controlling for fathers' and spouses' social class indictors, mothers' social class indicators are significant predictors of the social class position of women. This abstract represents the content of the candidate's thesis. I recommend its publication. olmes Anderson 111

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ACKNOWLEDGEMENTS Thank you to my advisor, Dr. Richard Holmes Anderson for his help and patience. Thank you to the entire University of Colorado at Denver Department of Sociology for providing an exciting and challenging Sociology program, that encouraged me to persevere in my studies. Thank you to my husband, Julius Wagner, for his unflagging support.

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CONTENTS Tables ................................................................................................. viii CHAPTER 1. INTRODUCTION......................................................................... 1 2. LITERATURE REVIEW.............................................................. 10 A Brief Historical Overview................................................. 10 Measuring Social Stratification............................................. 13 Social Stratification Measurement and Women.................... 17 Subjective Class Identification.............................................. 29 Social and Occupational Mobility of Women ....................... 32 Socialization of Children....................................................... 35 3. METHODOLOGY........................................................................ 40 Data ........................................................................................ 41 Sample ..................................................................... ;............. 42 Variables and Indicators........................................................ 44 v

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Method of Analysis ......... ;..................................................... 50 Limitations ........................ ;.................................................... 52 Data Limitations........................................................ 52 Other Limitations....................................................... 53 4. DATA ANALYSIS ........................................................................ 56 Cross Tabulation Models for Comparing Women and Their Mothers' Work History, Years of Education, and Occupational Prestige..................................................... 58 Separate Regression Models of Effects of Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige on Women's Occupational Prestige and Subjective Class Identity................................................. 68 Combined Regression Models of Effects of Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige on Women's Occupational Prestige and Subjective Class Identity................................................. 73 Combined Regression Models of Effects of Women's Years of Education and Occupational Prestige and Mothers', Fathers', and Spouses' Years ofEducation and Occupational Prestige on Women's Subjective Class Identity..................... 78 Regression Models Effects of Women's Years of Education and Occupational Prestige and Spouses' Years of Education and Occupational Prestige on Women's Subjective Class Identity........................................ 83 Regression Models Comparing the Combined Effects ofMen's Years of Education and occupational Prestige and the Years of Education and Occupational Prestige of Mothers', Fathers', and Spouses' on Men's Subjective Class Identity......................................................................... 87 Vl

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5. CONCLUSION .............................................................................. 95 APPENDIX A. Chapter 4 Data Analysis: Complete Tables and Data .................. 105 BffiLIOGRAPHY ......................................................................................... 124 Vll

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Table4.1 Table 4.2 Table 4.3 Table4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8 Table 4.9 TABLES Work History of All Female Respondents and All Mothers* of Respondents from GSS 1973 and 1998........ ..................... 59 Percent of Women Who Work Who Had Mothers Who Worked* While They Were Growing Up Women 40 to 50 and 30 to 40, 1971-1978 and 1991-1998 ............................... 60 Years of Education of All Women and All Mothers of Respondents from GSS 1973 and 1998 ............................. 61 Effects of Mothers' Years of Education on Occupational Prestige Women 40 to 50 and 30 to 40 1972-1978.......... 63 Effects of Mothers' Years of Education on Occupational Prestige Women 40 to 50 and 30 to 40 1991-1998.......... 65 Effects ofMothers' Occupational Prestige on Occupational Prestige Women 40 to 50 and 30 to 40 1994-1998.......... 67 Correlation-Regression Analysis for the Relationship of Mothers' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 68 Correlation-Regression Analysis for the Relationship of Mothers' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 69 Correlation-Regression Analysis for the Relationship of Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 70 Vlll

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Table4.10 Table 4.11 Table 4.12 Table 4.13 Table 4.14 Table 4.15 Table 4.16 Table 4.17 Correlation-Regression Analysis for the Relationship ofFathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 70 Correlation-Regression Analysis for the Relationship of Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 71 Correlation-Regression Analysis for the Relationship of Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 and 30 to 40 1994 to 1998.......................................................................... 72 Correlation-Regression Analysis for the Relationship of Mothers', Fathers' and Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 1994-1998 .................................................. 73 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 30 to 40 1994-1998 .................................................. 74 Correlation-Regression Analysis for the Relationship ofMothers' and Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 1994-1998 .................................................. 75 Correlation-Regression Analysis for the Relationship of Mothers' and Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 30 to 40 1994-1998 .................................................. 76 Correlation-Regression Analysis for the Relationship ofMothers' and Fathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1994-1998 .................................................. 77 IX

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Table 4.18 Table 4.19 Table 4.20 Table 4.21 Table 4.22 Table 4.23 Table 4.24 Table 4.25 Correlation-Regression Analysis for the Relationship ofMothers' and Fathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1994-1998 .................................................. 77 Correlation-Regression Analysis for the Relationship ofMothers', Fathers', Spouses', and Women's Occupational Prestige to Subjective Class Identity Women 40 to 50 1994-1998.............................................................................. 79 Correlation-Regression Analysis for the Relationship ofMothers', Fathers', Spouses' and Women's Occupational Prestige to the Subjective Class Identity of Women 30 to 40 1994-1998.............................................................................. 79 Correlation-Regression Analysis for the Relationship ofMothers', Fathers', Spouses', and Women's Years of Education and Occupational Prestige to Subjective Class Identity Women40 to 50 1994-1998 ........................... 81 Correlation-Regression Analysis for the Relationship ofMothers', Fathers', Spouses', and Women's Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1994 to 1998.......................................................................... 82 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1972-1978 .................................................. 84 Correlation-Regression Analysis for the Relationship ofWomen's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1972-1978 ................................................. 85 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1991-1998.................................................. 85 X

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Table4.26 Table 4.27 Table 4.28 Table 4.29 Table 4.30 Table 4.31 Table 4.32 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1991-1998.................................................. 86 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige to Subjective Class Identity Men 40-50, 1994-1998................................... 88 Correlation-Regression Analysis for the Relationship ofMothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1994-1998 ................................. 89 Correlation-Regression Analysis for the Relationship ofMen's and Spouses' Years ofEducation and Occupational Prestige to Subjective Class Identity Men 40 to 50 1972-1978 .............................................................................. 90 Correlation-Regression Analysis for the Relationship ofMen's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1972-1978.............................................................................. 91 Correlation-Regression Analysis for the Relationship of Men's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 40 to 50 1991-1998.............................................................................. 92 Correlation-Regression Analysis for the Relationship ofMen's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1991-1998.............................................................................. 92 XI

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CHAPTER 1 INTRODUCTION With all of the many indexes for measuring occupational prestige and status that have been developed (Hollingshead 1949, Hodge, Rossi and Seigel 1964, Blau and Duncan 1967), there is a continuing failure to resolve the social status of individuals comparative to gender. Although gender issues have been a focus in Status Attainment Theory, there have been only weak efforts made to include separate data on females. Nearly all of the social stratification indexes used to measure individual and family social position are based on the supposition that the family is the unit of measurement and the data to be used are information gathered about the male head-of-household. The assumptions made in stratification studies continue to exclude women independent of their relationship to men. Those assumptions are, 1) that the family is the unit of measurement in social stratification theory, 2) that class position of the family is determined by the status of male head of family, 3) that class position of a female is determined by the status of the male head of the family of which she is a member, and her status is the same as the male. (Acker 1973) 1

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Conventional Social Stratification Theory assumes that women can have their own status only when they are not attached to a family with a male head of household. However, in the last half of the Twentieth Century, many demographic and economic changes have affected the social status of women. Since the feminist movement in the 1960s, there is increased interest in exploring women's issues, and studies have found numerous elements that should be included when measuring women's social position, such as, changes in family composition and size, increased educational attainment, full time participation in the labor force, higher occupational mobility, gender differences in occupations, equal pay for equal work issues, as well as a socially acceptable decrease in male obligation to fmancially care for and support women. These areas of study are important cultural changes that should be considered when measuring individual social status separate from a woman's husband's class identity. Let us look at three of these issues. First, the definition of family has changed radically in recent years. The conventional view for measuring women's social stratification does not address these changes in family composition. The traditional nuclear family of husband/wage earner, housewife/mother, and children all living in the same household, while still the majority of households, is no longer the reality for many families in the United States. Since the 1960 U.S. Census, the number of female-headed households has almost doubled from 2

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9.8 percent to 17.6 percent. Women today are less likely to marry, more likely to marry later, and more likely to divorce, according to the 1990 U.S. Census, which also shows that children are five times more likely to be born to an unwed mother, and almost three times more likely to live in a female-headed household than they were in 1960 (Gilbert and Kahll993, p. 290). While this change is due in part to the greater tolerance of unwed motherhood and divorce, it is, nevertheless, a change in family composition that affects family social position. Second, paid employment and income reduces a woman's dependence on her husband's social class position when identifying her own class position. "As a woman's income increases, both in absolute terms and in relation to her husband's income, she may rely more on her own situation to defme for class identity." (Baxter 1994, p. 222) The percentage of employed married women has risen from about 25% in 1950 to more than 50% by 1985, and over 60% by the year 2000. (U.S. Census) Full time paid employment would give women a different perspective of social position than it does for women who work part time or not at all. Third, although the marital selection process today places more emphasis on educational homogamy (the attitudes about and aspirations for educational attainment that have become intergenerational characteristics of social position) a number of studies (Baxter 1994, Abbott 1987, Jackman and Jackman 1983, 3

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Hyman et. al., 1975, Kalmijn 1991) show that a woman's educational attainment is important to her in determining her social position. Jackman and Jackman found that a wife's level of education was a better predictor of her class identification than was her husband's educational attainment. According to Baxter, the more education and the higher occupational prestige a woman has the more likely she is to decide her social position independently from her husband. Baxter suggested, ... that husband's class alone provides an incomplete account of subjective class identity ... (p. 233) In her 1994 study, she showed that the husbands themselves were more likely to determine their class position by including their wife's employment status (p. 222-230), and yet, no accommodation has been made to include women's social status indicators in the indexes measuring family social class. Haller (1981), Acker (1973, 1980), Simpson et. al. (1988), Lockwood (1994), and Scanzoni (1978) are among those who have discussed methods to include gender in measurement of social status. Haller ( 1981) maintains that the, ... essence of social stratification concerns the intergenerational and intragenerational reproduction ... through homogamous marriage patterns and status inheritance over families and generations." (789) He believed in the possibility that social position may not be just, ... one marrying pair and its children but a sequence of marital and familial units ... (p. 779) This study will 4

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demonstrate that this is so. However, Haller did not follow through on intergenerational family social status as a possible avenue towards a more gender neutral measurement of social position, and even now in the year 2002, the problem has not been resolved. In books as recent as the late 1990s, such as Social Stratification (1996), by Daniel W. Rossides, gender inclusion measurement in social stratification is not directly addressed. In Social Class and Stratification: Classic Statements and Theoretical Debates (1998), David Lockwood points out that when discussing the disadvantages of the continuing use of the conventional method for measuring social stratification, "The fact that something should be of concern to the Equal Opportunities Commission does not thereby guarantee its sociological relevance." (p. 195) He suggests that occupational prestige ranking is a reliable method for measuring social position because, forthe most part, occupational prestige is "sex-neutral." By sex-neutral he means, that the subjective ranking of status of occupation is indifferent to whether a male or a female fills a job. This is not to imply that the various occupations themselves are sex-neutral. In studies of job prestige, the rating system is highly subjective and jobs held by women are usually rated lower than those jobs held by men. We know that women are represented exceptionally high in some of the lower middle class occupations, 5

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such as the service and clerical sectors, and oft times, the higher the percentage of women in a job, the lower its rating. In another study, Scanzoni (1978) discusses the dilemma of how to integrate gender differences into class stratification. He felt that combined income could be used as a measure of family social position, but found that the strongest predictor of a couple's social position was a combined score made up of "external resources." (p. 67) Scanzoni defmed external resources as, "skills or capabilities that generate goal attainment in systems outside the family, especially the occupational system ... (p. 25) He was also speaking of intangible innate leadership and organizational skills. These intangible skills enabled a family to utilize their resources to attain and maintain higher social position. Joan Acker, who has had an abiding interest in women and stratification since the 1970s makes a case for using the individual rather than the family as the unit of measurement and for finding a method to cross-reference the data collected on husbands and wives, but she did not devise a method for cross referencing data. It has become imperative to fmd a valid, replicable measurement of marriage and gender differences that could be incorporated into stratification research. Along with women's increasingly independent social class indictors, there are unique features and kin influences of family-of-origin that affect 6

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individual social position that could give a more accurate picture of social position of females besides husbands' class location. While it may not completely explain women's social position, one possibility for measuring women's social position is through mothers' status attainment indicators and the intergenerational occupational mobility that women share with their mothers. Using more information about mothers to determine social class would provide the benefits of a better measure of socio-economic status by including the mothers' occupation rather than just fathers' occupation. Research shows that when a mother works, her daughter is more likely to work, to work continuously and to choose an occupation that is less typically female. (Rosenfeld, p. 37) Mothers' occupation represents an adult role model, particularly to daughters, which could have an effect on the occupational choices of all children. Women should insist that their input be counted. That it is still not so, suggests that we have not "come a long way baby," and that there are underlying factors that create problems for changing how social stratification is measured. Among those factors are, first, many of the studies on social class positioning are done by asking the respondents own opinion of their social class but go no further. Unless, as Scanzoni (1978) demonstrates, women are questioned about how their real or perceived ideas of their social class affects their ranking, it may be that women's culturally socialized subjectivity about gender equality interferes 7

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with their answers. Second, using data that measures social position of the male head of household alone simplifies the management of resources and fimding from government agencies and other organizations. Third, there are those, like Goldthorpe, who are complacent about the existing methods of measuring social status. Their social stratification research reflects their failure to adapt to the changes in attitude towards gender and status. For this reason, the validity and continuing application of prior analysis and earlier conclusions of social stratification using the family unit with only data of the male head ofhousehold is debatable. While professionally sociologists ftgree that modifications need to be made in how social stratification is measured, allowing for the independent status that women have achieved, the modifications have yet to be done. Inquiry into social stratification should not ignore the intergenerational and intragenerational patterns of reproduction of social status. If, beyond certain gender related jobs, who is doing the job does not affect the prestige of the job, then Blau and Duncan's Socio-Economic Index could continue to be an accurate assessment of an individual's social position. Measuring class status by family unit remains a viable option, but needs to be expanded to include the intergenerational characteristics that Blau and Duncan observed. This thesis asserts that the concept of social class position cannot be understood apart from the educational and occupational achievements of family of origin. Because of 8

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the strong socializing influence that mothers have on their children, mothers are an important feature in measuring social status. Including mothers' work status, years of education, and occupational prestige to measure women's social position might prove to be a more accurate indicator of social status than now used. In this paper, characteristics of mothers' social position, such as years of education and occupational prestige are utilized to examine how these indicators affect women's social position through women's years of education, occupational prestige, and subjective.class identification. 9

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CHAPTER2 LITERATURE REVIEW A Brief Historical Overview Social stratification, an individual's position in his or her society and how that position is achieved or ascribed was, early on, an important topic of sociological debate. Emile Durkheim, the earliest structural-functional sociological thinker proposed that as societies progress, they also evolve, and this evolution moved societies toward more social complexity and differentiation. Complex societies became increasingly characterized by diverse and specialized roles for individuals. Durkheim proposed that much of that diversity was the result of occupational specialization. However, from occupational specialization there developed certain rights, such as the right to own property, to control labor, and to receive political favor. These rights eventually became a part of an individual's on-going social position. Durkheim believed that social equality and opportunity would be the result of occupational opportunity, but to the contrary, the social characteristics he thought would create equality are the same characteristics that created distinct social classes. Stratification formed because of the access individuals had or did 10

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not have, through educational and occupational achievement to wealth and power, and through ascribed characteristics, such as religion and ethnicity. Rather than creating equality, the economics of occupational specialization created social stratification with resulting inequalities. Durkheim did not accept that societies were economic systems with inherent inequalities and his hope of equality was simply idealistic dreaming. Were it not for Marxian Conflict Theory, social stratification might not have focused almost exclusively on the socio-economic inequalities of class, and instead focused on the social structures and functions of class. Karl Marx (1818-1883) and Max Weber (1864-1920) expanded on the economic aspects of society and class. To Marx the economic structure created divisions of labor and ownership of property that caused class formation. Weber agreed with Marx that there were economic causes in the formation of social class differences in society, but he elaborated on the reasons for class differences by proposing that there were also non-economic, socio-cultural factors that affected social stratification. Some of these socio-cultural influences are the social and cultural capital that comes from family beliefs and values, and access to political and legal influence. These socio-cultural characteristics tend to create boundaries that restrict others from entering one's own social class as well as inhibiting one's involvement with other classes. 11

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To the economic factors of class, that affect social position, Weber added 'status,' cultural influences that also affect social position. According to Weber, it was when the socio-cultural power of status was perpetuated generationally that social stratification developed. It is important to note, that the early sociological theorists were convinced that social stratification was an intergenerational phenomenon. In recent years, for the most part, this has been ignored when collecting data on social stratification. The Oxford Dictionary of Sociology defines social stratification as, ... systematic inequalities between groups of people, which arises as the unintended consequences of social processes and relationships." (1998, p. 643) The study of social stratification focuses on the differences between statuses, and the openness between statuses in a society. According to Matthijs Kalmijn, ... the openness of society is ... (measured by) ... how much people from different status groups interact on the basis of equality ... (1991, p. 497) Social stratification has been examined by a number Twentieth Century theorists, including P. A. Sorokin (1927), Erin Olin Wright (1987), Kingsley Davis and Wilbert E. Moore (1945), Gerhard Lenski (1966), Anthony Giddens (1973), Peter B1au and Otis Dudley Duncan (1967). They have analyzed social stratification from several differing perspectives. These are: the economic perspective which includes occupation, income and wealth (Wright, Lenski, 12

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Giddens); the status perspective which includes personal prestige, associations and socialization (Kingsley, Davis and Moore, Giddens); the political perspective which includes power and class consciousness (Lenski, Wright); and the social mobility perspective (Sorokin, Blau and Duncan). Measuring Social Stratification The most definitive of the recent work that measures social stratification is that of Peter Blau and Otis Dudley Duncan, with the publication of their book, The American Occupational Structure ( 1967). Their understanding of social attainment dynamics, presumed that social stratification is a handed-down, intergenerational social trait continued by, what they perceived as the most important variable, occupational prestige. Blau and Duncan proposed that individual occupational position is a good measure of an individual social position. The occupational prestige measurement they used was based on public opinion of occupation, and because of general subjective perceptions of what is considered an 'important' job and what is an 'unimportant' job, there is .some bias built into the measurement. Even the wording used for an occupation can influence the prestige of the occupation. For example, the job, druggist or pharmacist, even though the same, are subjectively .seen as pharmacist being a more important prestigious occupation than druggist. (Fussell 1983 p. 161) The 13

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prestige ofan occupation is more or less measured by how much power, trust, and authority the occupation gives an individual, and to some extent, this is separate from the income and educational indicators of social position. Fussell points out that, "the degree of supervision" one receives or gives in an occupation may be a better measurement of occupational status than either income or education. (p. 48) Blau and Duncan's theory of social mobility is notable, because they were able to devise a quantitative methodology for measuring social position that is still in use today. In 1967, using education and income, they created the "Socio economic Index of All Occupations" (SEI). This index has proved to be extremely reliable measurement of ranking prestige of occupations. They theorized that individual social position had its origins in: (1) The social position or class that an occupation is in; (2) Ascription, the ability to move between classes based on social barriers such as race, ethnicity and gender; (3) Intergenerational mobility, a relationship between the individual's social position to that of the parents, and; (4) Intragenerational mobility, how individuals own work status shifts them into different social positions over time. Blau and Duncan considered that attaining status might be an ongoing sequence of events, and that most occupational prestige and social position can be perpetuated intergenerationally by the ability to acquire education and assets. 14

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This perpetuation becomes a two edged sword when we realize that the ease or difficulty of acquiring education and assets depends upon the social position that an individual already possesses. While they conceded that social position was intergenerational, their study was limited to father and son generations only. Using the SEI to demonstrate social mobility, which is explained as, "The movement, usually of individuals but some times ofwhole groups, between different positions within the system of social stratification ... (Oxford, p. 422) Blau and Duncan used regression analysis to fmd a correlation that explained to what degree sons' social position was related to fathers'. The independent background variables they used for their analysis were fathers' education and fathers' occupation. They explored how fathers' occupational position affects the occupational position of sons. If, as they hypothesized, status attainment was an evolving condition, then examining sons' education, sons' first, and sons' current occupation as dependent variables, would show the longitudinal changes that they predicted. Measuring along a time line beginning with the fathers' education, fathers' occupation when the son was sixteen, the number of years of the sons' education, the prestige of the sons' first job, and the prestige of the sons' current job, they found an intergenerational correlation. Blau and Duncan's study explained that the social status influence of one generation on the next was a sequence of events over time. They showed that by knowing fathers' occupational 15

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position and educational attainment one could predict with reasonable accuracy the occupational position of sons. Social attainment in American society is not entirely explained by the influence of one generation's education on the next generation's education and occupation. It is important to point out that this effect does not relate only to obtaining education, but relates also to "which" education is acquired. The school attended by the fathers as well as the sons makes an enormous difference in how the education is advantaged with the subsequent occupational prestige and social position. There are also other difficult to measure indicators of status position such as political stance and social connections. Going a step beyond this, Gruskey and Sorensen, make a case for measuring social status by taking ... contemporary patterns of collective action ... into account, such as trade unions and associations, rather than just, ... aggregating technically similar occupations ... (1998 p. 1224) Other studies replicating and expanding upon Blau and Duncan's work followed on the heels of their study. One replication, the "Wisconsin Socio Psychological Model of Socioeconomic Achievement" by Sewell and Hauser (1972) used in addition to fathers' education and occupation, background characteristics such as fathers' income, mothers' education and family income. The Wisconsin analysis showed that there was a significant effect of mothers' 16

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education and fathers' occupation, income, and education on sons' occupation similar to Blau and Duncan's original study. Other studies using variables such as educational and occupational aspirations and peer interaction help to give further indication of the influences on status attainment. These studies confirmed that intergenerational features of family-of-origin were decisive influences on individual social status. Unfortunately, today the collection of data on social stratification primarily uses only indicators for individual education, occupation, and income. Social Stratification Measurement and Women Studies replicating Blau and Duncan were conducted using education, occupation and income data on the American male and give a reasonable and reliably accurate assessment ofthe socio-economic status of the male population, but not for the female population. No discussion of social stratification and gender would be complete without including work done by John H. Goldthorpe, particularly his 1983 paper, "Women and Class Analysis: In Defence of the Conventional View." Goldthorpe has been adamant that occupational position of the male head-of-household is the best measure of social position for females as well. Even into the 1990s, he persisted in being one of those who emphasized the entrenched structure of class and failed to account for the social changes of the 17

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last several decades. In his 1983 study, he vigorously defended the position that the family is the best unit of measurement for social stratification. He proposed that since there were continuing, universal gender issues such as division of household labor and availability of employment opportunities; and because families pool their resources and share consumption patterns, class position should be designated according to husbands' status characteristics. This conventional viewpoint goes back to Durkheim's Structural Functional Perspective, which maintains that all social institutions, including marriage, have particular purpose for maintaining the balance in society. From the theorizing of Parsons, Goldthorpe points to three distinct reasons for support of the functional perspective. He relates, 1) that the family must be considered a single unit for the solidarity of its members, 2) that there needs to be a basic equality of family members to maintain social position and, 3) that in most societies, only one family member is able to have a total commitment to the occupational system. (p. 466) His reasoning was that gender inequality is not the cause but the reason to support the conventional view. He maintains that by using the male head-of-household to measure status, women are actually elevated to a higher status position than they would otherwise be if measured on their own socio-economic merit. (p. 469) Goldthorpe interpreted data from several studies 18

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to mean that even if a woman was employed she was still dependent upon her husband. (1983 p. 468) The structural functional point of view helps to explain historically why the social position of the family has always been fixed by the status of the male as head of family; why it is assumed that females live in a family headed by a male and; why a female's status remains the same as the male head of family. This perspective seems no longer viable when we consider the major social changes that have occurred that affect women. Unfortunately, the continuing use of Goldthorpe's essay as the gold standard of support for the conventional view is outmoded when we consider that it was published in 1983 and the data were from a previous study done a decade earlier in the mid 1970s. The real progress toward equality for women in the United States began in the early part of the Twentieth Century. Females were gradually gaining autonomy from their fathers or husbands. They were allowed to own property, to vote, and judged capable of raising and supporting their children. Back then, no one considered the possibility that women could do all this and still hold a job. Until then, women from the day of their birth were considered the 'property' of their father and continued to be a part of their father's household until they married, when they became the 'property' of their husband. If women were not allowed to own property or vote, and few had an occupation of their own, there 19

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was little reason to include data about women in any measure of social class. By the end of the Twentieth Century however, a majority of women worked and many had educational and occupational levels equal to their husbands'. The late Industrial Revolution affected women and employment in two ways. First, supposedly women were freed from the overwhelming burden of household maintenance with the development of modern appliances, such as refrigerators, electric stoves, and washing machines. Second, the industrial revolution needed the influx of large numbers of workers to operate manufacturing machinery and women were accepted as factory laborers. Large numbers of women, as wage earners, is a relatively new concept in the United States. In 1890 less than 5% of married women worked. Even fifty years later in 1940, the number was still only 16% (Davis and Robinson 1988, p.1 04). By 1968, the number had risen to 35.5% (DeJong, et al. 1971, p. 1033), and by the year 2000 over 61% of women were in the labor force. (U.S. Census) Viewed in this light, it is understandable why social stratification studies dismissed the socio-economic position of women. However, the perception of the family as a single unit has become an antiquated notion by our modem assessment of what constitutes a family unit. Recent studies show the gender gap as narrowing but as Gurin says, ... the economic fates and claims to prestige of men and women are inextricably intertwined." (p. 145) In the past, ascribed 20

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characteristics, such as family connections, had the greatest effect upon whom one married, but in the last half of the Twentieth Century marital choice for both men and women in the United States changed to a preference for certain achieved characteristics. Educational attainment is an achieved characteristic that has had great impact. In a 1975 study, Hyman et. al., showed there is a negative relationship between educational attainment and choice of marriage partner. He explained that as a person's educational attainment increases, the chances of that person marrying someone with low educational attainment decreases, even if they have similarities in social class. In "Status Homogamy in the United States," (1991) Matthijs Kalmijn also showed that ascriptive marriage partner choice for individuals used to be to marry someone from one's own social class, but by comparing studies of status homogamy he showed that ... the correlation between spouses' education is stronger than the correlation between spouses' class origins." (p. 500) Educational institutions not only provide couples with educational equity, they also have an effect on values, attitudinal characteristics, and life-style preferences. Kalmijn found that the association between education and marriage partner selection increased for all cohorts in his study. It is reasonable to assume that educational attainment and the subsequent occupational prestige have become an important factor in the process by which males and females choose a marriage partner with 21

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its consequent social status. A recent poll from the E.W. Scripps School of Journalism at Ohio University shows a direct relationship between education and marriage. (Hargrove p. 75) The more education people have the more likely they are to be married. For males as well as females, two-thirds of those with a college education were married, while less than half of those with only a high school education were married. Educational attainment as a characteristic of social position has consistently been important for men, it seems it is now important for women also. In 2000, the nwnber of women who have at least a college degree though rising still does not equal the number of degrees obtained by men. In 1970, for every ten males having at least a college degree, six females had at least a college degree. In the year 2000, for every 10 males who have a college degree, there were approximately eight females who have at least a college degree. (U.S. Census) With all the gender based social changes that have taken place in the last 40 years, there has been some interest in studying how women's roles affect their social stratification (Acker 1978 and 1980, Grusky and Sorensen 1998, Baxter 1994, Haller 1981, Scanzoni 1978, Sorensen 1994, Davis and Robinson 1988). All agree that how social stratification is measured needs to be modified to reflect the independent status that women have obtained. In Davis and Robinson's 1988 study of the subjective class identity of married men and women, they used three 22

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models of identity. In the "independence" model, social class is identified by individual characteristics of both men and women separately. The "sharing" model gives equal weight to the characteristics of both spouses. The "borrowing" model detennines class by only the characteristics of the spouse, usually the male. This is seen, ... as a continuum ranging from one's own characteristics as the sole detenninant of one's class position ... throughjoint detenninants that include spousal characteristics, to viewing one's own characteristics ... as, unimportant relative to those of a spouse." (p. 1 05) They found that men were gradually becoming more accepting of the "independence" model and women were becoming more inclined to accept the "sharing" model rather than the "borrowing" model of previous studies. This shows that it is not only changes in gender role attitudes but also women's recent social and economic autonomy and newly discovered awareness of their position that gives them awareness of socio-economic equality. Gender consciousness for women has moved their perceptions to questioning, ... the legitimacy of gender disparities ... (Gurin, p. 156) With women using their successes as role models, they are no longer accepting that men are better qualified for particular jobs or are more ambitious than women. That men accept the "independent" model shows they also have become more gender conscious. That is, while the men may not be crediting spouses with 23

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contributing to the men's social status, they do credit the women with contributing to their own social status. Gurin found that men have changed their perception of power so much that by 1983 there was little difference of opinion between men and women. (p. 160) Gender consciousness also encompasses some amazingly fast changes in social attitudes and role expectations for women in recent decades. The social acceptance of non-traditional female behavior has changed the mother/adolescent daughter relationship. Tallichet and Willits (1986) found that the higher a mother's educational attainment, the more liberal were her attitudes. When the daughters matured, they were more likely to have higher educational attainment, were more likely to work, and were less likely to marry young. That a woman should derive her own status from her own accomplishments seems to be an idea whose time has come. There have been numerous studies suggesting how it might be possible to measure women's social position separately from men's, but none of them incorporate intergenerational family-of-origin characteristics. Using the Symbolic Interaction Perspective, Max Haller (1981) suggested that to understand the use of family as the fundamental unit of social stratification, one must first understand that marriage itself is a stratification relationship and next, must understand how this relationship is affected by the separate "acting units", the husband and the 24

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wife. (p. 775) The way to do this, he proposed, is to divide marital homogamy in social position measurement into two separate variable classifications, social stratification and social class formation. Social class formation becomes the public sphere of workers and managers, production and distribution, solidarity and competition. Social stratification then becomes the private sphere of individual and collective identity, relationships, and interactions. fu a homogamous marriage the couple would show a preference for sharing a wide range of characteristics such as intelligence, values, religion, race, and social class. Haller points out that couples in homogamous marriages are less likely to divorce. A likely affect of less divorce would be the perpetuation of intergenerational family social status. In an article published in 1980, Joan Acker reviews literature dealing with women and stratification. For her, existing theories do not adequately explain women's social position. She felt that to separate research into two types, such as Haller suggested would only create more confusion about where women stand in relation to social class. Others (Chafetz, 1974; Walum, 1977; Blumburg, 1978) have proposed separating stratification into sex and class divisions, but Acker was concerned whether this perspective could give an accurate picture of the socio economic position of women, because theories of sexual inequality and socio economic inequality though defmed by different issues can not necessarily be 25

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separated in social stratification. As she points out, ... sex stratification always involves economic and power inequalities ... that are a product of the existing social system. (p. 26) Other stratification models Acker discusses are the Dual-Economy/Labor Segmentation Theory, Marxist Market Economy Theory, the Feminist Paradigm, and Social Mobility Theory. Dual-Economy Labor-Segmentation Theory explains gender differences in social standing as differences in the core and periphery sectors of the economy, meaning that whether an individual's occupation is considered white collar or blue collar or has authority or no authority makes a difference in society's perception of the subjective ''value" of that individual. Periphery labor may be perceived as having less value than it really does and core labor perceived as having more value than is the reality. To understand social status and gender, we need to understand that many of the female-centric occupations tend to be in the periphery, which have lower occupational prestige. Marxist Market Economy Theory proposes that women's' position in the class structure is the result of capitalism needing a reserve labor pool and that labor pool is unequally made up of women. The thinking is that if there are more workers than the system can absorb, then workers have less value in the labor 26

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market. The large influx of women into the service type of jobs and the low pay they receive is an excellent example. The Feminist Paradigm expects that all measure of social position should be on an individual basis regardless of marital status. However, using the Feminist Paradigm for measuring social status and completely abandoning the idea of the family as the unit for stratification and class analysis, presents its own difficulties. Measuring each individual separately according to his or her occupational prestige would not provide an accurate measure of family class position, a measurement needed for understanding the distribution of resources. Using information about both husband's and wife's occupational position would be a start towards a combined measure of social position, but it is difficult to rate occupations in such a way that the combined score would accurately represent the husband's and the wife's family social position. For example, using the three divisions of the socio-economic index variable of occupational prestige created for the data exploration in this study (10-36=low SEI, 37-67=middle SEI, and 68-89=high SEI), if the husband is a dentist with SEI of74 and the wife is a social worker with SEI of 52, the mean becomes SEI 63 or a middle occupational prestige. This is probably not an accurate representation of the family's social position, although, because studies show that husband's occupational prestige 27

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score has more effect on the perceived family social status than the wife's, it might be possible to weight the husband's SEI score to show the greater effect. Ideally, some type of modification to the conventional way is needed to determine a family's social position. Sorensen (1994) suggests two possibilities, a "head-of-household" form of measurement, and a "joint classification" form of measurement. "Head-of-household" measurement, while similar to the conventional view, could be modified to designate as head-of-household, ... the person with the dominant occupational position," (p. 30) or designate the person who has the, ... greater influence on the family." (p. 40) Her "joint classification" model would, ... combine information about both husband's and wife's occupational class into a joint measure of family class position ... (p. 41) Of all of the proposals for a dual measurement of family social class, John Scanzoni may have come the closest to discovering spousal perceptions of social class, except that like others, he does not include family-of-origin. In his book, Sex Roles, Women's Work and Marital Conflict (1978), he uses secondary data from a previous study (Latunann and Senter, 1976) to show how wives' employment and income can affect subjective class placement. Using as variables only information about husbands (the conventional measurement of family social status), working and non-working women were asked to decide social class solely on information about their husbands. Husbands' income was the variable that had 28

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the most influence on selection of class position by wives, followed by job prestige and standard of living (economic satisfaction). However, after including the women's employment and income, women were able to distinguish between social position attained by their husband's contribution alone and the higher social position attained when their own contributions was included. (p. 68) Subjective Class Identification The existence of class has its foundation in Marxist Theory, but class distinctions are not as clear-cut and obvious as Marx predicted they would become in modem industrial societies. Although there are large differences in class just as Marx expected would occur, between owners of the means of production and workers, post-industrial American class status is chiefly measured by three socio-economic indicators. They are, 1) individual years of formal education from none through post graduate years, 2) occupational prestige score as measured by any ORe of the accepted indexes (this study uses Blau and Duncan's Socio-Economic Index of All Occupations, known as SED and, 3) income, usually an ordinal measurement ofincome defmed by dollar amount categories from low to progressively higher amounts. These three indictors are used primarily because their characteristics are so easily measured quantitatively. In reality, class identification is almost entirely a subjective interpretation of 29

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where one fits into the social hierarchy. Individuals make personal choices about where they themselves fit, and as much as we claim objectivity, our choices about where others fit is quite subjective as well. Richard Centers studied the subjective interpretation of social class in 1949, and Mary R. Jackman updated his study in 1979. When measuring social class, one would expect that the class categories would have clear definitions; that is, what is meant by upper class, middle class, working class, and lower class, etc., but they do not. Jackman points out that there are undefined cultural characteristics that, although are difficult to measure, such as beliefs and lifestyle but are, nevertheless, subjectively used to defme social class. This difficulty in measuring intangible characteristics is almost entirely the reason that class stratification has come to be measured by occupation, income and education (1979, p. 459). As Julie Mitchell explains, ... through out history, biological differentiation of the sexes ... and the division oflabor ... (1998, p. 175) have helped to explain the gender disparity that exists when measuring male and female social status. The subjective nature of class identification through occupation, education, and income has been dominated by male characteristics. Identifying the social class of the female by the social class of the male has been the customary way to measure family social class in our culture. This 30

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conventional view has become flawed since women have begun to assess their class position on their own merit. Scanzoni shows that the influence of women working and the increased family income has a significant effect on subjective class identification. In his 1978 study, women were asked ifthere was a, ... positive impact of wife working on class ... When the women responded positively, they were asked to subjectively assess what the difference in class would be. A new variable was then created in which class position was based on the composite input of both husband and wife. (p. 66) A mean score of 1.97 (high working class) was obtained for subjective class position when only husbands' input was considered, but this climbed to 2.22 (lower middle class) when joint input was used. Even with non-working wives there was a positive influence on perceived impact on lifestyle when asked what the effect would be if the woman was currently employed. Other studies confmn that class identity is in part subjective (Simpson, et. al. 1988 and Davis and Robinson 1988). Each found that if women worked, they were less likely to borrow their class position from their husband. Scanzoni goes on to speculate how a wife's income could effect household class position. He proposed that the effects could involve consumption behavior, wives using on the job skills to manage their household budget more successfully to obtain status goods. For example, he suggests that wives of factory workers 31

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who might consider themselves working class could use their money managing skills, ... in such a way as to attain what they considered to be a middle-class lifestyle. 11 ( 63) The use of extra income could be used to aid their husband's occupational activities such as entertaining work peers and to influence work place superiors. Household status could also be affected by wives using their own on-the-job work skills to advantage social position in situations outside the family and work environments by creating social capital. Social and Occupational Mobility of Women Acker believes that to adequately measure social stratification, 11 ... a sex integrated treatment of class stratification ... 11 (1980, p. 33) must be developed. She sensed that the Social Mobility Perspective could have the most possibilities for developing a gender-neutral measurement for social stratification. She says that, "In spite of differences in mobility patterns between the sexes, the most consistent fmdings are that occupational and marital mobility patterns of women are not much different from those ofmen ... (p. 27) Studies of social status as measured by intergenerational occupational mobility have focused almost exclusively on fathers and sons. One study explored what occupational mobility pattern could be expected by studying fathers and daughters. This 1971 study by De Jong, Brawer, and Robin shows 32

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that the occupational mobility between fathers and daughters is similar to that between fathers and sons, and would suggest that there could also be similarities between mothers and daughters that might be significant. They also point out that if women are obtaining patterns of occupational mobility similar to men they could be deriving similar levels of social status from their occupations. Comparisons of occupational categories, as in a study done by Rachel Rosenfeld in 1978, show that at that time, daughters did have a tendency to end up in occupational categories similar to their mother's, but her study was limited because her goal was to show sex similarities in occupational attainment between mothers and fathers and their daughters. She was not pursuing alternative methods of measuring socio-economic status. Other studies explored the effect of husbands' occupational mobility on women's mobility. In a study done in 1974, Tyree and Treas called this "marital mobility." (p. 297) They found that women had a tendency to move from their fathers' occupational category to a category similar to husbands' when they married. This study shows that today, women are more likely to identify with their mothers' occupational category than with their fathers'. In "Five Decades of Assortative Mating," Robert Mares made an interesting observation on choice of marriage partner. He proposed that women's increasingly career oriented participation in the labor force may be changing 33

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men's expectations of what constitutes a good marriage partner. He explains that, ... if men increasingly see women as breadwinners as well as mothers and homemakers ... then men ... will seek women who have the best earnings potential." (1991, p. 17) This would be separate from a man's own earning potential, and certainly have an effect on measuring social status. Other studies (Baxter 1994, DiMaggio and Mohr 1985), show that there is a trend towards increased educational assortative mating practices. Another reason for educational homogamy in marriage could be competition among men to marry women with good earnings potential brought about by their educational attainment. Max Haller supports Mares when he suggests that women with good earnings potential are being sought by men with both high and low educational attainment, and given the choice, women would most likely many men who also had good earnings potential, thereby maintaining or increasing their socially stratified class level. Haller goes on to say that increased educational attainment for women also reduces, ... the need for relying on marriage as an institution of maintenance and at the same time increases expectations about a marital partnership." (Haller, p. 782) The problem with past studies of social stratification is that they did not explore new avenues for predicting women's status attainment. They used data on fathers and husbands for measurement and even when data on mothers was used, 34

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it was to compare mother/daughter job categories not to measure social status. It seems obvious that the problem with measuring social stratification by using only data about the male head-of-household and the family as the unit for measurement does not go far enough to obtain an accurate measure of family social position. To obtain an accurate measure family social status, we must cast the net wider. Socialization of Children If we limit our measurement of social status to the occupation, income, and education of the head-of-household to obtain social position, but ignore the on-going persistent family status over several generations, we ignore the economic and cultural capital that increases one's ability to maintain social position. Symbolic Interaction Theory can help to explain social position if we include data on characteristics from family-of-origin. Symbolic Interactionism focuses on the ways people give meanings to things in the world around them through interaction with others. Those meanings are internalized and become a part of the individual's social life. Studies of the socialization of children show that, 11 the intergenerational transmission of attitudes ... and mother's attitudes in particular, are significant predictors of (children's) attitudes ... 11 (Bohannon 1999, p. 173) Major studies of maternal behavior and social class have proven conclusively that the mother is the primary socializing agent for her children. She 35

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is the most important element in giving meaning to her child's world. It is possible that mothers' social class also makes a difference in the methods of active socialization the mothers use. How do mothers' attitudes particularly affect their daughters? Studies of parentally transmitted attitudes (Adams 1967, Barber 2000, Acock and Bengston 1978, Arditti, Godwin and Scanzoni 1991, Jennings and Niemi 1982, Rollins and White 1982) have shown that daughters tend to internalize the attitudes of their mothers. For example, Barber's study (2000) on parents and childbearing suggests that the preference of when to have children is a socio-economic issue based on the prior socialization of the parents. Those in the lower classes who have less education, and non-working women prefer to marry young, have children at a younger age, and to have larger families. This would affect the eventual socio-economic choices of the children. Rollins and White ( 1982) showed that mothers influence the attitudes about career choices of daughters as young as 10 years old. When measuring influence of kin, Adams (1967) found that daughters consider their mothers the "prime movers" in their success as adults. {p. 369) De Jong, et. al., point out, ... occupational mobility is in part a consequence of continuity of employment ... {p. 1 034) It is possible that because of socialization, mothers' work history and occupation during children's growing 36

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up would have an effect on the work history and occupation of the children, particularly for daughters. An increased influence of maternal occupational prestige on daughters could be explained by the amount of upward mobility congruent with higher numbers of women in the work force. A study by Heyns and Catsambis in 1986, suggests that mothers' work history is very important to the achievement of children. They found that children's positive achievement was not so much affected by whether the mother worked or not, but affected more by the stable work history of the mother. If we assume that parental attitudes about occupation and education are internalized early in a child's life, then a mother's educational attainment and work experience would probably affect her methods of teaching her child. Employed mothers, especially those in high status occupations with greater job satisfaction, could be expected to encourage high achievement in their children. Such is the case according to Matthijs Kalmijn. In his study, "Mother's Occupational Status and Children's Schooling" (1994), he found that a mother's occupational status had a strong influence on her children's educational attainment, independent of a father's occupation. Mothers influence their daughters, and the daughters eventually influence their husbands, so it is worth noting that studies of occupational achievement of males (Rosen 1961; Mortimor and Lorence 1979; Heyns and Catsambis 1986; 37

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Kahnijn 1994) show that maternal influence on sons is also significant enough that it probably should be taken into account for all studies of achievement of males as well as females. In "Family Structure and Achievement Motivation," Rosen showed that a mother who dominates the decision making process is perceived as imposing her standards on boys, while fathers who are dominating are perceived as imposing himself on his sons. (1961, p. 575) When mothers make decisions they tend to try to enlist the cooperation of children rather than to just coerce them, this could be why, 11 mothers appear to promote the development of achievement motivation in boys. 11 (p. 577) Other studies of boys and mothers show that mothers' employment has a positive effect on sons if the mother is a high achiever as shown by her occupational prestige. (Scanzoni, p. 345) In fact, mothers are so influential in their children's educational and occupational success, studies show that single mother families, when employment status is taken into account, are second only to two parent homes in significance when measuring a child's socio-economic success. (Biblarz, et. al., p. 321) When we understand the strong influence that mothers have on their children, it becomes important to explore the effect mothers have on their children's social status. Since studies show an association between mothers' influence and occupation on sons as well as daughters, using data on mothers' 38

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occupational prestige could be the additional indicator we have been looking for to obtain a more accurate assessment of social stratification. I turn now to the exploration of the social class of mothers as measured by her years of education and occupational prestige, and how it affects the social class of daughters. At the end, data on men and their mothers, fathers, and spouses will be briefly examined to see if there is an additional effect on social class between these family members and men. 39

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CHAPTER3 METHODOLOGY To assess the affect that mothers have on women's social status, I explore the following questions, 1) How has work status changed for women and their mothers in the United States in the last three decades? 2) Is women's work status affected by mothers' work history? 3) Has women's and mothers' educational attainment changed in the last three decades? 4) Is women's occupational prestige affected by mothers' years of education and occupational prestige? 5) Is women's subjective class identity affected by the years of education and occupational prestige of mothers? If these indicators do affect women's occupational prestige, then it is important to see if they remain significant compared with the effect that fathers' and spouses' indicators have on women's social status, so the following inquiry is made. 6) Is women's occupational prestige and subjective class identity affected by the years of education and occupational prestige of mother, father and spouse? (7) How is women's occupational prestige affected by the years of education, and occupational prestige of only family-of-origin, the parents? 8) How is women's subjective class identity affected by their own occupational prestige as well as the 40

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years of education and occupational prestige of mothers, fathers and spouses? 9) How is women's subjective class identity affected by only her own and spouses' years of education and occupational prestige? 10) Is men's subjective class identity affected by their own years of education and occupational prestige as well as the years of education and occupational prestige of mothers, fathers, and spouses? 11) How is men's subjective class identity affected by his own and spouses' years of education and occupational prestige? Data For studying the effect mothers have on women's social class as measured by their years of education, occupational prestige, and subjective class identity, I selected 1972 through 1998 cumulative data from the General Social Survey. The GSS is a survey asking questions about a wide variety of social issues. The first year that the General Social Survey was conducted was 1972. It has been conducted in the United States at more or less regular intervals by the National Opinion Research Center in Chicago. GSS uses a national multistage probability sample to the block level. At the block level quota sampling is used based on sex, age, and employment status. (GSS Cumulative Codebook pg. 784) The sample of participants is chosen carefully and thoroughly so that the results are considered a representative and accurate assessment of the general American 41

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population. Every year that the survey is conducted, between 1000 and 2000 English-speaking male and female adults 18 years of age and older are asked questions in face-to-face interviews using the standard questionnaire method. There are three types of questions in the survey. First, there are permanent questions that appear every time the survey is conducted; second, there are rotating questions done every two to three years; and third, there are occasional questions prompted by current events in the year of the survey. Not all questions are asked of all the interviewees. To facilitate the interviews and still acquire as much data as possible, some questions are asked only of a sub-sample of individuals. Sample To explore the affect that mothers have, over time, on the social position of women, I selected a sample of females from an early time period, combining the 1972 through 1978 surveys, and from a late time period, combining the 1991 through 1998 surveys. The early and late time periods create sub-sets of women who have had similar life experiences, but the sub-sets are also far enough apart in years to show the effect of general cultural changes. Although the question about whether or not a mother worked while the respondent was growing up was not asked in 1972, I used 42

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six years to maintain an adequate number of respondents. The later grouping includes five years because there were no surveys conducted in 1992, 1995, or 1997. I divided the sample of females into two birth cohorts, from the early and late sub-sets. This created four birth cohorts in all, two between the ages of 40 and 50 years old and two between 30 and 40 years old. Birth cohorts are groups characterized by common experiences. By selecting women who are 30 years old or older, I can assume that they have been in the work force for a number of years and that they have had experienced some intragenerational occupational mobility. In this case, an early and a late birth cohort give a representation of not only the life experiences and occupational history of the women in my sub-set but also of their mothers by suggesting cohorts of the mothers. There are 21,417 female respondents in the GSS data from 1972 through 1998 with 5137 females ages 30 through 40, and 3854 females ages 40 through 50 in years. The combined surveys for the early and late groups yielded a sub-sample of 986 and 1434 women respectively 40 to 50 years old. For women ages 30-40, the sub sample size is 1250 for the early group, and 1770 for the late group. Because I was analyzing only women and their mothers, I did not focus on whether female respondents had children or if they or their mothers were single or married, excepting when looking for the effect that respondents' spouses' data might have on their social position. Whether or not a woman was married or had 43

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children might affect her social position, but was not a consideration in my analysis. I also did not focus on any racial or ethnic differences amongst the respondents. These fmer details of the lives of women and their mothers would be appropriate for further study of this topic. Because I briefly explore the effect that mothers', fathers' and spouses' social status indicators have on men, I use the same approach for sample selection that I used in selecting the sub-sets of women. That is, 1) I use the same two age cohorts, men age 40-50 years and men age 30-40 years, and; 2) I use the same year groupings, an early grouping, years 1972-1978 and a late grouping, years 1991-1998. The sample of males was taken from a total of 16,699 men in the GSS from 1972 through 1998. There are 877 males age 40-50 in years 1972-1978 and 984 males age 30-40 in years 1972-1978. In the years 1991-1998 there are 1192 males age 40-50 and 1402 males age 30-40. Variables and Indicators Upon exploration of the variables available in the GSS that could be used to measure female respondent's social position, I found years of education, degree attainment, income, occupational prestige, subjective class identity, marital status, work status, and rank to have possible use in my study. I selected these variables as useful because they are all relevant to social status. The social sciences primarily 44

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measure status using three primary indicators. They are years of education, occupational prestige, and income. These other variables listed, such as marital status, work status, and rank are all affected by the three primary indicators. For example, women's work status (part time or full time) can affect income, and income affects social status. In most cases, higher social class is indicated by higher income. Because this study is about the affect mothers have on women's social position, of further interest are variables pertaining to respondents' mothers. In the nearly 30-year history of the GSS, 18 questions have been asked that pertain to the relationship between respondents and their mothers. Most of these questions are not relevant to exploring mothers' effect on daughters' social position, such as "Is mother still living?" Several questions of interest but only asked one or two times between 1972 and 1998 are questions about, 1) Mothers working and closeness of relationship to child, 2) A comparison of the respondents and the parents standard of living and, 3) The amount of influence that women have in our society. Questions that were asked consistently from 1972 to 1998 that can be used to explore the effects of mothers' social class indictors on women's social position include, 1) What is mothers' work histmy, and did the mother work while respondent was growing up? 2) What are mothers' years of education? 3) A third question of importance for explaining the effects of mothers on women's social position is 45

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mothers' occupational prestige, but respondents were not asked a question about mother's occupation until 1994. In studying mothers' influence on women's social position it is important to make comparisons with the influence of fathers and spouses on women's social position. Data about respondents' fathers' and spouses' education and occupation were available for all years the GSS was conducted. I subjectively projected that the mothers were between the ages of 20 and 30 years old when the respondents were born. By projecting backwards, we can get approximate years of birth for the mothers. For example, the birth years of the mothers, for the older women 40-50, in the 1972 to 1978 group, would be about 1892 to 1918; and the birth years for the younger women 30-40 in the 1991-1998 group, would be about 1921-1948. Although years ofbirth for the mothers is quite a wide range1 year of birth could have an effect on whether or not mothers worked, their years of education, and occupational prestige. Combining separate variables for respondents' and spouses' occupational prestige was required to create a continuum of information. Respondents' and spouses' occupational prestige is presented in two separate variables, PRESTIGE and SPRES for surveys conducted 1972 through 1990 and PRESTG80 and SPRES80 for surveys conducted 1988 through 1998. Leaving the coding the same, I copied the 46

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data into one variable for respondents, PREST ALL and one variable for spouses, SPRESALL. Collapsing the occupational prestige variable for respondents was necessary for manipulating the data in cross tabulation analysis. Comparing the Occupational Classification Distributions (GSS 1972-1994 Cumulative Codebook, Appendix F, p.871-889), to fmd three categories that are a reasonably precise measurement of occupations that have low, middle, and high prestige, they were divided as, 1036=low prestige, 37-62=middle prestige, 63-89=high prestige. The following exemplify the low, middle, and high categories. The break between occupational prestige score 36 and 37 gives the occupations, clerical supervisors, counter clerks, meter readers and clothing ironers for 3 6, while occupational prestige score 3 7 describes dental laboratory technicians, protective services occupations, office machine repairers, and various types of machine operators. The break between occupational prestige scores 62 and 63 gives such occupations as optometrists and registered nurses at 62, and mathematical scientists and economists at a prestige score of 63. This division did not distribute the data into categories with equal frequency with the higher prestige category having the fewest number of cases. Collapsing some of the other variables is also necessary to do cross tabulation analysis. The years of education variables for respondent, and respondents' fathers, mothers, and spouses are recoded from twenty-one into three categories. Combining 47

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categories is necessary to obtain an adequate number of respondents in the higher education category. This produces variables measured as: 1) less than high school education, 2) high school graduate, and 3) at least one year of college. The variables are now ordinal in nature and require that the proper measures of association be used. For reasons that are not clear, the regression program seems unable to read correctly the coding of years of education that began with zero. Once these numbers were recoded into single digits, for example, one year of education from 01 to 1, regression analysis proceeded normally. The dependent variables are female respondents', 1) Work Status, defmed by whether she was working or had worked, 2) Years of education, used as both a continuous variable (from none through 20 years of education) and as an ordinal variable with three separate categories (less than high school, high school graduate, some college), 3) Occupational prestige, as measured by the Blau and Duncan SEI score, a subjective measure ranking occupations from 0 to 100 (although the lowest is 10 and the highest is 89) used as both a continuous and a recoded ordinal variable and, 4) Subjective class identity, as measured by Richard Centers, using four categories of class which are lower, working, middle, and upper. The independent variables are female respondents', 1) Mothers' work history, as measured by whether the mother worked or did not work while 48

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respondent was growing up, 2) Mothers', fathers', and spouses' occupational prestige, as measured by the Blau and Duncan SEI score, a subjective measure ranking occupations from 0 to 100 (although the lowest is 10 and the highest is 89) used as both a continuous and a recoded ordinal variable, 3) Mothers', fathers', and spouses' years of education, used as both a continuous variable (from none through 20 years of education) and as an ordinal variable with three separate categories (less than high school, high school graduate, some college). The grouping variables are, 1) Two specific year groups, 1972-1978 and 1991-1998 and, 2) Two birth cohorts, 40 to 50 year olds and 30 to 40 year olds. For measuring the effects of mothers', fathers', and spouses' social class indictors on men's occupational prestige and subjective class identity, I use the same social class indicators used for females. These are: mothers', fathers', and spouses' years of education and occupational prestige; as well as respondents' years of education, occupational prestige, and subjective class identity. Where needed these were recoded or combined into one variable in the same manner as those for female respondents. Method of Analysis My hypothesis is that mothers' work history, years of education and occupational prestige influence women's occupational prestige and subjective 49

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class identity. This study is a systematic analysis of social class position of women through her status attainment and intergenerational occupational mobility as measured by mothers' work history, years of education, and occupational prestige. In my basic model to explore the relationship between mothers' and women's social class, social position is operationalized by using the variables work history, years of education, occupational prestige, and subjective class identity that pertain to respondents and to mothers of respondents. Inclusion of data on fathers' and spouses' years of education and occupational prestige is used to-assess the independent effect of mothers' data. Grouping variables, birth cohort, and selected survey years, are needed in the analysis because of historical changes in women's and work experience, educational attainment, and occupational prestige in the last thirty years. It is expected that mothers' work history, years of education, and occupational prestige will all have a positive effect on the occupational prestige and subjective class identity of women and that this would subsequently affect women's social position. However, because numerous studies in the past argued for the traditional measurement of social class that measures women's social class by that of fathers and spouses (Goldthorpe, 1983; Sorensen, 1994; Baxter, 1994) the possible effects of fathers' and spouses' years of education and occupational 50

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prestige are investigated before detennining the over all effect from the mothers on the social class of women. By first doing cross tabulation analysis, I will see if there is a relationship between mothers' work history, years of education, and occupational prestige and women's work history, years of education, occupational prestige, and subjective class identity. The collapsed categories and new variables I created help reduce the number of cells that do not have adequate data or would otherwise be empty, affecting the validity of the results. Any relationships between mothers' years of education and occupational prestige and women's years of education, occupational prestige, and subjective class identity found in the cross tabulations, will be compared in linear regression models to determine the strength of the relationships and whether the relationship is positive or negative. The relationship between men's occupational prestige and subjective class identity and mothers', fathers', and spouses' years of education and occupational prestige is briefly explored to help us assess the over all strengths and weaknesses of the intergenerational indicators. 51

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Limitations Data Limitations The question of how mothers influence the social position of women can be answered only iJ! due to the confines of the GSS data set. There are, as with any data set, limitations to how the data can be manipulated and the information the data supplies. For my study, the data limitations found in the 1972 through 1998 surveys are: 1. As complete and representative as the GSS data set is, it is still an example of the biases against women by the social sciences. It was only in 1994 that the GSS first asked a question about mothers' job and computed the occupational prestige score. Until that year, occupational prestige score had been measured for respondents, respondents' spouse and respondents' father only. Having only three years of data on mothers' occupational prestige is a weakness in my study. It would have been very helpful to have many more years of measuring mothers' occupational prestige for a greater understanding of how mothers' occupational prestige affects the social status of children. This problem can be addressed in further studies using data where this information is supplied or by collection of new data. 52

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2. The GSS survey is administered only to English speakers, so the opinions of non-English speakers are lacking in the surveys. I made no direct attempt to include or exclude women of various races and ethnicity. 3. There seems to be no cross-referencing of respondents to see if other family members have participated in the past. I had no way of knowing if any of the women in my sample were related to each other but the effect would probably be so minimal that it would not affect the data. 4. As with any sutvey that uses a random sample, there is error in assuming the same percent of different individuals would answer the questions the same as the sample. This sampling error, while not to be taken lightly, can usually be ignored in this type of survey. 5. Because the GSS is a survey using a sample of the general population, there can be some problem created in assuming the data can be applied to the population as a whole. In most cases, it is safe to assume that the error would be so minor that it is ignored and the conclusions reached from the data are viewed as valid and applicable to the general population. Other Limitations 1. The SEI prestige scoring system of Blau and Duncan, was created using data on males alone, using a scoring system from a survey of subjective opinion 53

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of occupational prestige. It has long been debated if these scores apply to females as well. I agree with Lockwood that occupational prestige goes with the occupation not with the gender, in as much as the occupation itself is gender neutral, such as doctor or accountant. However, the problem remains that some occupations simply are not gender neutral. This is responsible for some subjective bias that certain occupations are less prestigious than the equivalent male counter part. This bias may be evident in the number of women in my sample who are in the three occupational prestige levels. I did not attempt to make any adjustments for this. 2. I am aware that there can be certain problems in the scoring system of the SEI. It works reasonably well when all scores are used in intenral measurement, but can have some inconsistencies when turned into categories and used with ordinal methods of measurement, such as I have done in cross tabulations. 3. I am also aware that measuring respondents' social class using mothers' occupational prestige does not account for the occupational prestige of mothers who are not in the workforce. Although some attempts have been made (Bose, 1973; Treiman and Terrell, 1975) to create a category of "homemaker" and create an appropriate occupational prestige score, so far no standardized score has been accepted in the social sciences. 54

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4. When creating the dichotomous variables of mothers' and women's work history, I did not take into account whether or not work was part-time or full-time. Studies show that women who work part time are less likely to have high prestige jobs. I am aware that this could make a difference in the occupational prestige scores of the women and the mothers. 55

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CHAPTER4 DATA ANALYSIS The first objective of this analysis of measurements for women's social status is to do simple comparisons of women's and mothers' social class indicators, by using cross tabulations to discover if mothers' work history, years of education and occupational prestige have any association to the work history, years of education, occupational prestige, and subjective class identity of women. If there is a relationship, then it is important to create linear regression models and explore the strength of those relationships. However, before we can be certain that mothers' social class indicators do positively affect women's social position, we need to understand separately the associations between a woman and the other prominent people in her life, namely, her father and spouse. The second objective is to compare fathers' and spouses' years of education and occupational prestige separately to examine any positive or negative associations and the strength of the associations to women's occupational prestige and subjective class identity. If associations are found between a woman's social class indictors and those of her mother, father and spouse, it is important to analyze the strength of the social class indicators from the mother, father, and spouse. Therefore, I will compare 56

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women's occupational prestige to the years of education and occupational prestige of mothers, fathers and spouses. In recent years, women are more inclined to consider their own social class indicators when measuring their social class. The third objective, then, is to create linear regression models comparing women's own years of education and occupational prestige together with mothers', fathers' and spouses' years of education and occupational prestige to women's subjective class identity. By using linear regression models, it is possible to compare the strength of each association independent of the others. However, because we are seeking intergenerational influences on women's social status, the fourth objective will be to compare women's occupational prestige and subjective class identity to only mothers' and fathers' years of education and occupational prestige. Past studies claim that even if women are giving more strength to their own social class indictors, they are still primarily measuring their social class position by their husband's social status indicators. The fifth objective will compare women's subjective class identity with their own years of education and occupational prestige and that of their spouses, to see if this is still the norm. If the traditional method of measuring social status, using male head of household as the measurement for family class is still valid, then women's social class indictors of years of education and occupational prestige should not be significant to 57

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men's perspective of their own subjective class identity. The sixth objective is to see if wives are influencing how men measure their own subjective class identity, by first, comparing men's subjective class identity with their own years of education and occupational prestige and that of mothers, fathers, and spouses, and then by comparing men's subjective class identity with their own years of education and occupational prestige and that of their spouses only. Some of the tables in the following analysis have been edited to emphasize the relevant data. Complete tables can be found in Appendix A. Cross Tabulation Models for Comparing Women and Their Mothers' Work History, Years of Education, and Occupational Prestige By examining the data on female respondents and the data available on their mothers, several conclusions can be reached about the effect of mothers' work history, years of education, and occupational prestige on daughters. The division of women into birth cohorts and then into an early and a late year category gives a more historically clear picture of the cultural context in which the mothers as well as their daughters were born, attended college, and were in the work force. The following tables show that mothers do have influence over women's occupational prestige and subjective class identity and that the influence has grown stronger in recent years. 58

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Table 4.1 Work History of All Female Respondents and All Mothers* of Respondents from GSS 1973 and 1998 All Women 1973 Number of Respondents I I I I I I I Women Who Work or Have Worked (Percent saying yes) 46.0% 347 All Women 1998 : 79.5% NumberofRespondents : 1212 *Data on mothers work history not available for year 1972 Mothers Who Worked (Percent saying yes) 48.1% 331 62.3% 923 Looking at women's participation in the labor force, in Table 4.1 we see the increase in women who work or have worked and, the increase in mothers who worked, for ALL women in the General Social Surveys from 1973 to 1998. As we can see, the number of women in the labor force increased by 72% between 1973 and 1998. How does the increase in women working compare with the percent of mothers who worked? The number of mothers who worked increased by nearly 30% from 1973 to 1998. By 1998 over 60% of women had mothers who worked or had worked at sometime in their lives. These figures closely agree with U.S. Census data, that show in 1970, 38% of women worked, but by the year, 2000 about 60% of all adult women were in the labor force. Knowing that there has been an increase in the number of women in the work force is an important feature of the change in how women measure their social status. 59

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In Table 4.2, the older cohort, age 40-50, 1973 through 1978, at 49.6%, had a 1 in 2 chance to be working and to have mothers who worked while they were growing up. Table 4.2 Percent of Women Who Work Who Had Mothers Who Worked* While They Were Growing Up Women 40 to 50 and 30 to 40 1973-1978 and 1991-1998 Women Who Are Working (Percent saying Yes) I 1973-1978 I 1991-1998 Mother Worked Birth Cohort 40-50 1 49.6% 1 67.7% Number of Respondents I 207 I 755 I I I I Mother Worked Birth Cohort 30-40 I 67.3% I 76% I I Number of Respondents 1 334 1 955 *Data on mothers work history not available for year 1972 The percentages of women and mothers working or not working are fairly evenly distributed over the four possibilities (see Appendix Table 4.1a). However, there are significant changes that occur between the birth years of the younger cohort and the older cohort. We see that, of women age 30-40 in 1973-1978, over 67% of the women who worked had mothers who also worked. For years 1991-1998, both birth cohorts show an increase in the number of women who work who had mothers who worked while they were growing up, ranging from nearly 68% for the women age 40-50, to 76% for the women age 30-40. In just a few years, the women who work with mothers who worked while they were growing up increased progressively from 1 out of2, to 2 out of3, to 3 out of 4. 60

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The greater numbers of women in the labor force has a parallel effect through the process of women's increased years of education that would also influence women's occupational prestige and subjective class identity. As we can see in Table 4.3, for ALL women respondents in 1973 and 1998 in the General Social Survey the number of women who have at least one year of college increased nearly 125 %from 23.1% to 51. 7%. This table shows that for ALL women the number of mothers with at least one year of college also increased by 125%, from 11.8% to 26.9%. Table 4.3 Years of Education of All Women and All Mothers of Respondents from GSS 1973 and 1998 Women Who Completed At Least One Year of College (Percent saying yes) Number of Respondents Mothers Who Completed At Least One Year of College (Percent saying yes) Number of Respondents i All Women 1973 All Women 1998 23.1 186 11.8% 72 51.7 824 26 9% 363 This is understandable in the historical context of the decades when the mothers would have attended college. The mothers of the older birth cohort would have attended college from about 1910 to 1930, while the younger mothers of the younger cohort would have attended college between approximately 1940 and 1960. U.S. Census data show there was a 150% increase from 1940 to 1970 in the number of American women 25 years old or older who have at least some college education, and between 1970 and 2000, the increase was 329% (U.S. Census) 61

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Whether or not a woman works or has educational opportunities is undoubtedly a response to issues other than whether or not her mother worked. One possible factor is that children of working mothers may tend to be more independent, which could have the effect that a daughter was more likely to work as an adult. Other influences on whether a woman works or not would be economic necessity, being a single parent, and, of course, the time-phased job mobility acquired by the increased years of higher education. That women, over time, increased their years of education could demonstrate that they are applying new opportunities to their work experience. The number of women and mothers who are in the work force has increased rapidly in the last half of the twentieth century. Whatever the reason that mothers and daughters are obtaining more years of education and participating in the labor force, they are establishiilg occupational prestige for themselves. Because education and occupation function as indicators of social status, the increase in years of education and occupational prestige women and their mothers are making, logically should be making a difference in their own social status. It would seem predictable that mothers' increased years of education would have an affect, over time, on the occupational prestige of women. If we look at the highlighted figures in Tables 4.4, we see that of the women who had mothers who did not complete high school, 76.5% of the 40-50 year olds and 67.9% of the 30-40 year olds have occupations that are in the low prestige category. 62

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The mothers who have at least one year of college have few daughters who are in the low prestige category, only 4.6% and 6.2% respectively. Table 4.4 Effects of Mothers' Years of Education on Occupational Prestige Women 40 to 50 and 30 to 40 1972-1978 Occupational Presti e Score of Women Women Age 40-50 Women Age 30-40 Low : Middle : High : M th Y f P lp lp I o ers ears o restlge : resttge: restlge: Education 10-32 : 37-62 : 63-89 : Total -------------------------T-------r------r-----Low : Middle : High : P lp lp I restlge: resttge: resttge: 10-32 : 33-62 : 63-89 : Total 1 I I I bid Not Complete High School 76.5% 56.7% 34.6% 65.4% 67.9% 42.5% 32.1% :53.9% High School Graduate 18.9% I I I I I I 27.0% 30.8% 23.3% 25.9% 40.6% 28.6% :33.5% At Least One Year of College Total Percent Number of Respondents 4.6% 100% 349 16.3% 100% 356 34.6% .11.4% I I 100% : 100% I 26 I 731 I I I I I 6.2% 16.9% 39.3%:12.6% I I 100% 100% 100% h 00% I 452 503 28 I 1524 In Table 4.4, looking at the highest occupational prestige category for women 40-50 years of age, we see that 34.6% have mothers whose years of schooling includes at least one year of college, and of the 30-40 year olds women 39.3% have mothers who have some college education. One thing of note about Table 4.4 is that the women with high occupational prestige are fairly evenly distributed regardless of the years of education of their mothers. I believe this consistency parallels the educational and occupational opportunities available to women in recent decades that were not available to the mothers. 63

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For both birth cohorts in Table 4.4, 1972-1978, only about 12% of the mothers had at least one year of college education. Census figures support this data. In 1940, the year on average, the mothers would have been finishing four years of college, less than 4% of women had at least four years of university education. In 1970, 8% of women 25 years old or older had at least four years of college, and data from the most recent census of 2000, show that the number of women with at least four years of college is over 23% of the general population (U.S. Census). Opportunities for women increased dramatically between 1970 and today. If we look at Table 4.5 showing women by birth cohort in 1991-1998, we can see that the differences in mothers' years of education compared to daughters' occupational prestige gradually ameliorate from the 1970s to the 1990s. In Table 4.5, for the youngest birth cohort, women age 30-40 in the years 1991-1998, about 34% of women who had mothers that did not finish high school remain in the lowest occupational prestige category. This is about half the number as shown in Table 4.4 for the 1970s. In Table 4.4 and 4.5, of the women who had mothers who fmished at least one year of college, the number of women 40-50 in the highest prestige category increased to 37.1% from 34.6% and for women 30-40 from 39.3% to 42.5%. For women age 40-50 in 1991-1998, the number of mothers with some college education doubled to 23%, and for the younger cohort, age 30-40, it nearly tripled from 12.6% to 30.1 %. 64

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Table4.5 Effects of Mothers' Years of Education on Occupational Prestige Women 40 to 50 and 30 to 401991-1998 Occupational Presti! e Score of Women Women Age 40-50 Women Age 30-40 Low l Middle l High l Low l Middle l High l Mothers Years of Prestige! Prestige! Prestige! Prestige!Prestige!Prestige! Education 10-32 l 37-62 l 63-89 l Total 10-32 l 33-62 l 63-89 l Total -----------------------r------T-------T-----------,------,-------r-------Did Not Complete High School 49.0% 31.9% 24.9% 35.9% 34.3%, 21.7% 17.1% 25.3% High School Graduate 38.7% 44.1% 38.0% 41.4% 43.9% 46.3% 40.4% 44.6% At Least One Year o College 12.4% 24.0% 37.1% 22.7% 21.8% 32.0% 42.5% 30.1% Total Percent 100% 100% 100% 100% 100% 100% 100% 1100% NumberofRespondents 388 653 221 1262 522 774 228 I 1524 As Table 4.5 shows, by the 1990s, the members of the ymmger birth cohort are more evenly distributed in the prestige categories and the mothers have more years of education. Both are significantly augmented by the increase in high school graduation levels of mothers. If we look back at Table 4.4, we see that in the 1970s only about 23% of mothers of the older women had a high school diploma, by the 1990s in Table 4.5, nearly 45% of the mothers of the younger birth cohort had graduated from high school. I think it is safe to say that in the last thirty years, mothers with more education have had a positive effect on the amount of education that daughters obtained. In Tables 4.4 and 4.5, we fmd a direct relationship between mothers' years of education and women's occupational prestige. With better education, women are 65

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able to obtain higher occupational prestige, and this would have a decisive affect on how their social status is measured. The more education the mother has the more likely her daughter is to be in the highest occupational prestige group. Mothers' increased education has to affect daughters' social status. This seems to be such convincing proof of the effectiveness of mothers' educational attainment on daughters' socio-economic success, that one wonders that there shouldn't be an ad campaign encouraging young women to go to college if only for the sake of their future daughters. An additional effect on women's occupational prestige besides mothers' years of education is the influence that mothers' occupational prestige has on women's occupational prestige. It should be noted that in Table 4.6 and any other tables using mothers' occupational prestige, the data are from GSS years 1994, 1996, and 1998. Asking respondents mothers' occupation and measuring mothers' occupational prestige score has been a part of the General Social Survey questionnaire only since 1994. Even in this limited amount of time, however, the data show that mothers' occupational prestige is an influencing characteristic affecting women's occupational prestige. Particularly obvious in Table 4.6 is that the majority of women who have low prestige occupations have mothers who also had low prestige occupations, over 72% of women 40 to 50 years old and 56% of the women 30-40. Conversely, of the 66

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women 40-50 with low prestige jobs, only 5.6% have mothers with high prestige jobs; and of the women 30-40, with low prestige jobs, only 7.1% have mothers with high prestige jobs. Table 4.6 Affects of Mothers' Occupational Prestige on Occupational Prestige Women 40 to 50 and 30 to 40 1994-1998 Low Occupational :Middle Occupational I High Occupational Prestige 10-36 Prestige 37-62 Prestige 63-89 I I I I Occupational Prestige Women Women Women Women Women Women Score of Women 40-50 30-40 1 40-50 30-40 1 40-50 30-40 ----------------------Low Occupational Prestige 10-32 72.3% 55.7% 22.1% 37.1% 5.6% 7.1% Middle Occupational Prestige 3 7-62 49.9% 41.4% 38.6% 47.1% 11.5% 11.4% High Occupational Prestige 63-89 28.4% 32.2% 43.1% 47.5% 28.4% 20.3% Total Percent 24.6% 45% 34.3% 43.8% 12.4% 11.2% Number of Res ondents 339 368 218 358 79 92 As explained by child socialization processes, children who have mothers who are high achievers tend to be high achievers themselves. Higher achievement for daughters is no doubt also affected by greater acceptance of women's contemporary gender roles. Before the case can be positively stated for inclusion of data about mothers into measurement of social stratification, it is important to understand how mothers' influence compares to the influence of women's fathers and husbands. 67

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Separate Regression Models of Effects of Mothers'. Fathers', and Spouses' Years of Education and Occupational Prestige on Women's Occupational Prestige and Subjective Class Identity While it seems undeniable that mothers influence the years of education and occupational prestige of daughters and thusly women's social prestige, it is likely that the effect of fathers and spouses influence is also a factor in measuring women's social status. In Tables 4.7 through 4.12, I regress separately the dependent variables women's occupational prestige and subjective class identity against mothers', fathers', and spouses' years of education and occupational prestige to test the strength and direction of effects. Table4.7 Correlation-Regression Analysis for the Relationship of Mothers' Years of Education and Occupational Prestige to the Occupational Prestige Women 40 to 50 and 30 to 401994-1998 Women40-50 Women 30-40 Standard : : : ized : 1 Standard : : Independent Coefficient: : Correlations ized :Correlations Variables s Signifi Zero Partial Coefficients : Signifi! Zero Partial Mothers' Years ofEducation .149 .002 .262 .128 .107 .011 .196 .092 Mothers' Occupational Prestige .197 .000 .283 .168 .163 R .308 .239 R .095 I .057 Regression eoeffieient slgnllieant at p>.OS, two tailed test. 68 .000 .221 .139

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Although subjective class identity is an ordinally measured variable, in all the following tables, it has been handled as an intervally measured variable. We see in Table 4. 7 that according to the Beta coefficients, mothers' years of education and occupational prestige by themselves are both significant in influencing women's occupational prestige for both birth cohorts. In Table 4.8, when women's subjective class identity is regressed on mothers' years of education and occupational prestige, although the amount of effect from the beta weights is similar, it is mothers' years of education that is significant to the older birth cohort, and mothers' occupational prestige that is significant to the younger birth cohort. Table 4.8 Correlation-Regression Analysis for the Relationship of Mothers' Years of Education and Occupational Prestige to the Subjective Class Identity Women 40 to 50 and 30 to 40 1994-1998 Women40-50 Women 30-40 I I I I I I I I Standard : : Standard : : Independent ized : 1 : Correlations ized : : Correlations I I I Variables Coefficients: Signifi: Zero Partial Coefficients: Signifi: Zero Partial ___ __ Mothers' Years ofEducation .185 .000 .234 .155 .037 .381 .141 .031 Mothers' Occupational Prestige MultipleR R2 .086 .245 .060 .072 .192 .071 Regression coefficient significan at p>.OS, two tailed test. 69 .188 .210 .044 .000 .208 .158

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In Table 4.9, comparing women's occupational prestige with their fathers' indicators for women in both age cohorts, it is fathers' years of education that is significant. For the younger cohort fathers' occupational prestige is also significant. Table 4.9 Correlation-Regression Analysis for the Relationship of Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 and 30 to 40 1994-1998 Women40-50 I I I I Standard I I Independent ized ! Correlations Variables Coefficients I Signifi I Zero Partial I I ____ __ __ -----Fathers' Years of Education. Fathers' Occupational Prestige MultipleR R2 .208 .063 .247 .061 .000 .242 .177 .130 .176 .054 Regression coefficient significant at p>.OS, two tailed test. Women 30-40 I I I I Standard I I ized ! Correlations Coefficients I Signifi I Zero Partial I I (Beta) 1 cance 1 Order _________ J_ _____ .173 .140 .277 .077 .000 .251 .148 .000 .237 .120 Table 4.10 Correlation-Regression Analysis for the Relationship of Fathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 and 30 to 40 1994-1998 Women 40-50 I I I I Standard I I Independent ized ! Correlations Variables Coefficients I Signifi I Zero Partial ____ -----Fathers' Years of Education .259 .000 .288 .222 Fathers' Occupational Prestige MultipleR R2 .055 .292 .085 .167 .195 .049 Regression coefficient significant at p>.OS, two tailed test. 70 Women30-40 I I I I Standard I I ized ! Correlations Coefficients I Signifi I Zero Partial (Beta) I cance I Order .205 .000 .23 7 .1 73 .057 .242 .059 .144 .172 .049

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In Table 4.1 0, fathers' years of education has the strongest effect. It is significant to the subjective class identity of both birth cohorts, and the Beta for fathers' years of education for the older women at .259 is the strongest influence so far. The R-squared in Tables 4.7 through 4.10 show that fathers' and mothers' indicators have similar strength and women are deriving only a modest amount of their social status from parents individually. This tells us only a small part of the story; we know from previous studies that husbands' social class indictors also have an effect on the social class of their wives. Tables 4.11 and 4.12 compare women and their spouses. Table 4.11 Correlation-Regression Analysis for the Relationship of Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 and 30 to 401994-1998 Women40-50 I I I I Standard : : Independent ized ! Correlations Variables Coefficients: Signifi: Zero Partial ___ spouses' years ofEducation .270 .000 .378 .236 Spouses' Occupational Prestige .188 .000 .343 .167 Multiple R .408 R2 .167 Regression coefficient significant at p>.OS, two tailed est. 71 Women30-40 I I I I Standard : : ized ! Correlations Coefficients: Signifi: Zero Partial (Beta) : cance : Order ------.206 .000 .328 .176 .207 .000 .328 .177 .368 .135

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Table 4.12 Correlation-Regression Analysis for the Relationship of Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 and 30 to 40 1994-1998 Women40-50 I I I I Standard I : Independent ized ! Correlations Variables Coefficients: Signifi: Zero Partial ------Spouses' Years of Education .360 .000 .458 .317 Spouses' Occupational Prestige .170 .000 .378 .156 R .427 R .229 Regression coefficient significant at p>.OS, two tailed test. Women 30-40 I I I I Standard : I ized ! Correlations Coefficients I Signifi I Zero Partial (Beta) : cance I Order ------.355 .000 .428 .304 .124 .003 .333 .111 .439 .193 In both Table 4.11 and 4.12, spouses' years of education and occupational prestige are significant in influencing women's occupational prestige and subjective class identity for both birth cohorts. The Beta weights suggest that the strongest individual influence on women's class identity comes from spouses' years of education rather than from mothers or fathers indictors. These separate regressions of mothers', fathers', and spouses' years of education and occupational prestige, while significant have only moderate influence. For both birth cohorts it would seem that women are not deriving their social class position from their husbands, as strongly as previous studies would have us believe; and the younger women are slightly less affected by their spouses' indicators than the older women. 72

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Combined Regression Models of Effects of Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige on Women's Occupational Prestige and Subjective Class Identity m this analysis, it is important to create an all inclusive model of the independent variables, of mothers', fathers' and spouses' years of education and occupational prestige, and the dependent variables, of women's' occupational prestige and subjective class identity, to test the strength of parental and spousal indicators when regressed against each other. In Table 4.13, for the older birth cohort it is mothers' occupational prestige and spouses' years of education that are significant to the occupational prestige of the older women. Table 4.13 Correlation-Regression Analysis for the Relationship of Mothers', Fathers' and Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 1994-1998 Standardized : Correlations Independent Variables Coefficients : 1 Zero Partial ____ __ --------Mothers' Years of Education .111 .149 .292 .091 Mothers' Occupational Prestige .183 .013 .303 .156 Fathers' Years of Education -.034 .638 .204 -.030 Fathers' Occupational Prestige .038 .565 .187 .037 Spouses' Years of Education .290 .000 .373 .252 Spouses' Occupational Prestige .043 .539 .252 .039 Multiple R .455 R2 .207 Regression coefficient significant at p>.OS, two tailed test. 73

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Fathers' indictors have no significance, and in fact, as shown by Beta, fathers' years of education appears to have a negative impact on women's occupational prestige. The strongest effect on women's occupational prestige is Beta at .290 from spouses' years of education. For women in the younger cohort, in Table 4.14, it is fathers' and spouses' occupational prestige that are significant to the measurement of women's occupational prestige. Of the beta coefficients, at .172, variation in spouses' occupational prestige has the strongest effect on changing women's occupational prestige. Table 4.14 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige to Occupational Prestige Women 30 to 401994-1998 Standardized : Correlations Coefficients . : Zero Partial ----------------------------___ ____________ Mothers' Years of Education .073 .278 .234 .062 Mothers' Occupational Prestige .031 .638 .225 .027 Fathers' Years of Education .080 .246 .288 .066 Fathers' Occupational Prestige .143 .025 .299 .128 Spouses' Years of Education .105 .115 .301 .090 Spouses' Occupational Prestige .172 .008 .308 .152 Multiple R .418 R2 .174 Regression coefficient significant at p>.OS, two tailed test. These-tables show that for the older women, it is mothers' that affect women's occupational prestige and for the younger women it is fathers who have an effect, but in both cases it is spouses who have the most effect. 74

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To continue to explore the intergenerational influences on women's social status, I temporarily discard the data on husbands. This gives a better understanding if data on mothers is becoming significant and should possibly be included in the indicators measuring social status. Tables 4.15 and 4.16 present the results of women's subjective class identity regressed against only mothers' and fathers' years of education and occupational prestige. In Table 4.15 for women 40-50 years of age, of the parental achievements that are significant to women's occupational prestige it is mothers' years of education and occupational prestige that are important not fathers'. Beta coefficients show that variations in mothers' years of education and occupational prestige affect the occupational prestige of daughters. Table 4.15 Correlation-Regression Analysis for the Relationship of Mothers' and Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 40 to 50 1994-1998 Standardized : : Correlations Independent Variables Coefficients ! Zero Partial ___ Mothers' Years of Education .119 .042 .250 .094 Mothers' Occupational Prestige .184 .001 .276 .149 Fathers' Years of Education Fathers' Occupational Prestige Multiple R R2 .016 .058 .305 .093 Regression coefficient significant at p>.OS, two tailed test 75 .793 .274 .192 .166 .012 .049

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For women 30-40, Table 4.16, it is mothers' occupational prestige, fathers' years of education, and fathers' occupational prestige that are all significant for measuring women's occupational prestige, but these are not as significant as mothers' indicators for the older women, as shown in Table 4.15, and none ofthe Beta weights have as strong an influence as that for mothers' occupational prestige. Table 4.16 Correlation-Regression Analysis for the Relationship of Mothers' and Fathers' Years of Education and Occupational Prestige to Occupational Prestige Women 30 to 401994-1998 Standardized : Significance : Correlations Independent Variables Coefficients : : Zero Partial _________ Mothers' Years of Education .025 .638 .196 .020 Mothers' Occupational Prestige .1 05 .035 .209 .090 Fathers' Years of Education Fathers' Occupational Prestige Multiple R Rz .130 .129 .303 .092 Regression eoefficient significant at p>.OS, two taHed test. .015 .010 .253 .247 .103 .110 Obviously there are other factors influencing women's occupational prestige. I would suspect that because there are more women in the labor force today, women are apt to have more interest in parental occupational prestige as a measure of their social class. While parents are having some affect on women's occupational prestige, are they also affecting women's subjective class identity? Tables 4.17 and 4.18 explore 76

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women's subjective class identity in relation to parents' years of education and occupational prestige. Table 4.17 shows that both mothers' and fathers' years of education are significant to a woman's subjective class identity with fathers years of education showing the strongest direct relationship. Table 4.17 Correlation-Regression Analysis for the Relationship of Mothers' and Fathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1994-1998 Standardized 1 Significance 1 Correlations Independent Variables Coefficients I I Zero Partial I I ____ J ___________ Mothers' Years of Education .113 .050 .268 .090 Mothers' Occupational Prestige .070 .191 .227 .060 Fathers' Years of Education Fathers' Occupational Prestige Multiple R R2 .191 .028 .330 .109 Regression coefficient significant at p>.OS, two tailed test. .001 .586 .300 .192 .149 .025 Table 4.18 Correlation-Regression Analysis for the Relationship of Mothers' and Fathers' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1994-1998 Standardized 1 Significance 1 Correlations Independent Variables Coefficients I I Zero Partial I I _________ ____ Mothers' Years of Education -.074 .166 .115 -.059 Mothers' Occupational Prestige Fathers' Years of Education Fathers' Occupational Prestige Multiple R R2 .136 .184 .054 .259 .067 Regression coefficient significant at p>.OS, two tailed test. 77 .007 .001 .291 .181 .226 .178 .115 .142 .045

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For women 30-40, in Table 4.18, it is mothers' occupational prestige and fathers' years of education at that are significant to women's subjective class identity. The change from mothers' years of education to mothers' occupational prestige could possibly be explained as an effect of the increased numbers of career oriented women and mothers in the labor force. Combined Regression Models of Effects of Women's Years of Education and Occupational Prestige and Mothers', Fathers', and Spouses' Years of Education and Occupational Prestige on Women's Subjective Class Identity As we saw in the previous tables, the two age cohorts do not entirely agree about the effects of parental influence on their occupational prestige or subjective class identity, but when we compare women's subjective class identity to her own occupational prestige and that of mothers', fathers', spouses', the older and the younger birth cohorts are of the same mind about their subjective class identity. In Table 4.19, for women 40-50, their own occupational prestige and that of their mother and spouse are significant to women's subjective class identity. We see that fathers' occupational prestige is not significant. Spouses' occupational prestige has the strongest effect on women's subjective class identity, but interestingly, the beta coefficient of mothers' occupational prestige at 78

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.183, has more influence on women's occupational prestige than women's own occupational prestige at .117, in the selection of subjective class identity. Table 4.19 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses' and Woman's Occupational Prestige to Subjective Class Identity Women 40 to 50 1994-1998 I Standardized Correlations Independent Variables Coefficients I 1 Zero Partial rconstantl (Beta) I Significance I Order --------Mothers' Occupational Prestige .183 .002 .267 .185 Fathers' Occupational Prestige .050 .399 .216 .051 Spouses' Occupational Prestige .339 .000 .396 .344 Woman's Occupational Prestige .117 .045 .267 .122 MultipleR Rz .475 .225 Regression coefficient significant ot p>.OS, two toiled test. In Table 4.20, for women 30-40 years of age, again, it is their own occupational prestige and that of mothers and spouses that are significant to women's subjective class identity. Again, fathers' occupational prestige is not significant. While spouses' influence is still moderately strong at Beta .293, it should be noted that it has decreased and women's own occupational prestige at Beta .187 has increased causing it have more effect than it did for the older women as shown in Table 4.19. 79

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Table 4.20 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses' and Woman's Occupational Prestige to Subjective Class Identity Women 30 to 40 1994-1998 Standardized 1 Correlations Independent Variables Coefficients l 1 Zero Partial Mothers' Occupational Prestige .113 .03 7 .229 .113 Fathers' Occupational Prestige .012 .830 .182 .012 Spouses' Occupational Prestige .293 .000 .378 .292 Woman's Occupational Prestige .187 .000 .303 .189 Multiple R Rz .442 .196 Regression coefficient significant at p> .05, two toile test. The previous tables partially explain women's occupational prestige and subjective class position. This demonstrates that along with their own occupational prestige and that of their husband, for women, a mothers' occupational prestige is a factor in explaining how women determine their class position. The small R-squared tells us there are obviously other influencing factors affecting women's social class position, not least of which are other of her own social status indictors. We know that subjective class association is an individual's own perception of where they are in the status hierarchy and is a cognitive creation, so how does women's own years of education and occupational prestige affect subjective class identity along with mothers', fathers' and spouses' years of education and occupational prestige? 80

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In Tables 4.21 and 4.22, women's own years of education and occupational prestige and mothers, fathers and spouses years of education and occupational prestige are compared to women's subjective class identity. As we see in Table 4.21, when a 40-50 year old woman's subjective class identity is compared to her own years of education and occupational prestige and those of her mother, father, and spouse, it is mothers' years of education and spouses' years of education and occupational prestige that are significant factors affecting her subjective class identity. Table 4.21 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', and Spouses', and Women's Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to SO 1994-1998 Standardized 1 Significance 1 Correlations I I Coefficients l 1 Zero Partial _____ Mothers' Years of Education .170 .018 .364 .150 Mothers' Occupational Prestige .017 .808 .267 .015 Fathers' Years of Education .108 .110 .329 .102 Fathers' Occupational Prestige -.037 .545 .204 -.039 Spouses' Years of Education .217 .002 .461 .191 Spouses' Occupational Prestige .184 .005 .412 .177 Women's Years of Education .128 .083 .423 .110 Women's Occupational Prestige .020 .758 .292 .020 MultipleR .580 R2 .336 Regression coefficient significant at p>.OS, two tailed test. 81

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These eight indicators explain nearly 34% of women's subjective class identity in spite of the fact that fathers' years of education and occupational prestige continue to not be significant. It is important to point out that for this older birth cohort, their own indictors are not significant. This is possibly a telling example of the culturally socialized subjectivity that the older women used to measure their class identity. For the younger birth cohort in Table 4.22, we see that this has changed. Table 4.22 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses', and Women's Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1994-1998 Standardized I Correlations Independent Variables Coefficients ! Zero Partial ___________ __ Mothers' Years of Education -.033 .615 .136 -.029 Mothers' Occupational Prestige .090 .145 .207 .084 Fathers' Years of Education -.015 .820 .196 -.013 Fathers' Occupational Prestige -.049 .423 .162 -.046 Spouses' Years of Education .326 .000 .464 .261 Spouses' Occupational Prestige .143 .020 .386 .133 Women's Years of Education .036 .615 .346 .029 Women's Occupational Prestige .144 .013 .298 .142 MultipleR .515 R2 .265 Regression coefficient significant at p>.OS, two tailed test. In Table 4.22, for the younger cohort of women, it is not only spouses' years of education and occupational prestige that are significant in measuring women's subjective class position, but also these younger women are taking into 82

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account their own occupational prestige when determining their subjective class identity. For these younger women, their own occupational prestige is significant at .013 in their selection of their class position. While mothers' years of education and occupational prestige are not significant here, previous comparisons show that mothers' indicators do have an effect on women's own indicators. As this study shows in previous tables, women's years of education and occupational prestige are influenced by the years of education and occupational prestige of mothers. Regression Models of Effects of Women's Years of Education and Occupational Prestige and Spouses Years of Education and Occupational Prestige on Women's Subjective Class Identity If women's own class indicators are regressed only against those of spouses, do spouses' indicators remain as strong? The traditional method for measuring women's social class has been to use only data on male head of household. Studies using this perspective maintain that husbands' social status has the largest impact on women's social status and husbands' social class as measured by his socio-economic index is the best indicator of women's social class. This point of view maintains that even if women are giving more strength to their own social class indictors, they are still primarily "borrowing" their social class position using their husbands' social status indicators. (Goldthorpe 1983, 83

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Sorensen 1994, Baxter 1994, Simpson et. a11994). However, as this study has shown so far, the younger birth cohort of women 30-40, are beginning to use the "sharing" model and "independent" model to measure their social class using their own individual indicators. (Davis and Robinson 1988) In Tables 4.23 and 4.24, where women's years of education and occupational prestige are regressed against spouses' years of education and occupational prestige, we see that this effect continues. In Table 4.23 for the older birth cohort, women 40-50 in 1972 to 1978, it is only spouses' years of education and occupational prestige that are significant to subjective class .identity. Table 4.23 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1972-1978 Standardized : Significance : Correlations Independent Variables Coefficients : : Zero Partial __________ ___ women's Years of Education -.009 .864 .231 -.007 Women's Occupational Prestige .073 .131 .239 .062 Spouses' Years of Education Spouses' Occupational Prestige Multiple R Rz .151 .264 .407 .166 Regression coefficient significant at p>.OS, two tailed test. .004 .000 .336 .377 .119 .223 However, as we progress through the year groupings, from the younger women in 1972-1978, Table 4.24, to the older women in 1991-1998, Table 4.25, to the younger women in 1991-1998, Table 4.26, we see that women begin to 84

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measme their subjective class identity by their own years of education and occupational prestige. In Table 4.24, when women's subjective class identity is regressed against her own social status indicators and those of spouses, we see that spouses indictors are significant and still having the strongest effect on women's class identity, but women's years of education has become significant. Though the effect is small at a Beta coefficient of .1 00, it nevertheless shows women's new awareness to their own achievements when measW"ing their class identity. As data show, these are achievements that have a relationship to the achievements of their mothers. Table 4.24 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1972-1978 Standardized l Correlations Independent Variables Coefficients l Zero Partial __________ ____ _________ Women's Years of Education .100 .021 .335 .081 Women's Occupational Prestige .041 .302 .267 .036 Spouses' Years of Education Spouses' Occupational Prestige Multiple R -R2 .241 .153 .446 .199 Regression coefficient significant at p>.OS, two tailed test. .000 .000 .412 .362 .187 .131 By the years 1991-1998, Tables 4.25 and 4.26, for both the older and younger women, their own years of education are significant and continue to affect their subjective class identity. In Table 4.25, spouses' indicators are also 85

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significant, but women's years of education is significant and the beta coefficient has increased to .146 from .100. Table4.25 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 40 to 50 1991-1998 Independent Variable __________ ________ Women's Years of Education Women's Occupational Prestige Spouses' Years of Education Spouses' Occupational Prestige MultipleR R2 Standardized l Significance l Correlations Coefficients l l Zero Partial ___ JL ___________ .146 .001 .381 .123 .054 .170 .291 .050 .231 .185 .495 .245 .000 .000 .436 .392 .195 .171 Regression coefficient significant at p>.OS, two tailed test. In Table 4.26, showing the latest year grouping, 1991-1998, and the youngest birth cohort, 30-40, both women's years of education and occupational prestige have become significant to the women's class identity. Table 4.26 Correlation-Regression Analysis for the Relationship of Women's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Women 30 to 40 1991-1998 Standardized l Significance l Correlations Independent Variables Coefficients l l Zero Partial I I ___ -------Women's Years of Education .148 .000 .380 .123 Women's Occupational Prestige .123 .000 .318 .114 Spouses' Years of Education Spouses' Occupational Prestige Multiple R R2 .210 .121 .470 .221 Regression coefficient significant at p>.OS, two tailed test. 86 .000 .001 .401 .343 .176 .110

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When the Beta weights in Tables 4.25 and 4.26 are compared, we see that spouses' years of education and occupational prestige, while still significant are having a diminishing effect, as women's own years of education are having an increasing effect. Regression Models Comparing the Combined Effects of Men's Years of Education and Occupational Prestige and the Years of Education and Occupational Prestige of Mothers, Fathers, and Spouses on Men's Subjective Class Identity To have parental and spousal social class characteristics included in the measurement of social stratification, it is important that these characteristics be meaningful in their influence on both males and females; and before we can conclusively assume that mothers' social class indicators of years of education and occupational prestige are important factors in measuring women's social status, we need to look at how mothers', fathers' and spouses' social class characteristics influence males. To explore these issues, in the following tables, I replicate Tables 4.23 through 4.26, this time using data on men. Because conventional social class measurement uses male head of household to determine family social class, I look briefly at, 1) the affect that men's years of education and occupational prestige as well as the years of education and occupational prestige of mothers, fathers, and spouses have on men's subjective class identity; and 2) the effect that men's and spouses' years of education and 87

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occupational prestige alone have on men's subjective class identity. Again, we understand subjective class identity to be a self-orienting perspective of individual awareness of where one fits into the hierarchy of social position. When assessing family effects on class, studies continually maintain that men are primarily influenced by their fathers' and their own social status indicators. Tables 4.27 through 4.32 show that in recent years, this is no longer entirely true. In Table 4.27, for the older birth cohort of men age 40-50, it is men's years of education alone that is significant to men's subjective class identity, with fathers' years of education just outside significance at .054. These older men are defining their social class by their own occupation with little credit to the contributions of their mothers, fathers, or spouses. Table4.27 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige to Subjective Class Identity Men 40 to 50 1994-1998 Standardized 1 Significance 1 Correlations Independent Variables Coefficients I I Zero Partial ___________ ___ ____ j ___________ Mothers' Years of Education -.102 .204 .122 -.085 Mothers' Occupational Prestige -.072 .324 .098 -.066 Fathers' Years of Education .161 .054 .266 .129 Fathers' Occupational Prestige .102 .175 .256 .091 Spouses' Years of Education -.132 .076 .182 -.119 Spouses' Occupational Prestige .060 .358 .122 .062 Men's Years of Education .404 .000 .460 .312 Men's Occupational Prestige .118 .113 .371 .106 Multiple r .512 R2 .262 Regression coefficient significant at p>.OS, two tailed test. 88

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What is interesting in Table 4.27 is that the older men attribute their class identity only to their own indicators, but as we see in Table 4.28, the younger men attribute their class identity to fathers and spouses. In Table 4.28, for the younger birth cohort of men, age 30-40, the fathers' years of education has become significant to men's subjective class identity, and spouses' occupational prestige is now significant. Cwi.ously, men's own indicators are no longer significant in determining the men's subjective class identity. As shown by the Beta weights, wives' occupational prestige contributions the second largest influence to men's subjective class identity. Table 4.28 Correlation-Regression Analysis for the Relationship of Mothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1994-1998 Standardized I Significance I Correlations Independent Variables Coefficients ! Zero Partial ___ ____ Mothers' Years of Education -.082 .279 .190 -.067 Mothers' Occupational Prestige .005 .936 .153 .005 Fathers' Years of Education .227 .005 .339 .173 Fathers' Occupational Prestige -.010 .883 .214 -.009 Spouses' Years of Education .038 .614 .318 .031 Spouses' Occupational Prestige .199 .003 .311 .185 Men's Years of Education .142 .080 .359 .109 Men's Occupational Prestige .094 .190 .318 .081 Multiple R .463 R2 .214 Regression coefficient significant at p>.OS, two tailed test. 89

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To see if this effect continues, in Tables 4.29 through 4.32, I measure men's subjective class identity by comparing men's years of education and occupational prestige with only spouses' years of education and occupational prestige. The results are similar to the comparisons done for women and spouses in Tables 4.23 through 4.26. As we see in Table 4.29, for the older birth cohort of men in the years, 1972 to 1978, it is only their own years of education and occupational prestige that are significant to their subjective class identity. We should be reminded that as shown in Table 4.23, the older birth cohort of women in this same time period also measured their subjective class identity by the men's years of education and occupational prestige. Table 4.29 Correlation-Regression Analysis for the Relationship of Men's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 40 to 50 1972-1978 Standardized 1 Significance 1 Correlations Independent Variables Coefficients I I Zero Partial Men's Years ofEducation .184 .001 .383 .138 Men's Occupational Prestige .205 .000 .380 .165 Spouses' Years of Education Spouses' Occupational Prestige MultipleR R2 .067 .063 .429 .184 Regression coefficient significant at p>.OS, two tailed test. .200 .201 .289 .269 .054 .054 However, in Tables 4.30, 4.31 and 4.32, the younger birth cohort of men in 1972-1978 and both birth cohorts of men in 1991-1998, determine their 90

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subjective class identity from their own indicators and from their spouses' occupational prestige. First, in Table 4.30, for the younger birth cohort in 1972-1978, spouses' occupational prestige is significant at .021, and the Beta effect of spouses' occupational prestige on men's subjective class identity is .109. Table 4.30 Correlation-Regression Analysis for the Relationship of Men's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1972-1978 Independent Variables __________ ________ Men's Years of Education Men's Occupational Prestige Spouses' Years of Education Spouses' Occupational Prestige Multiple R R2 Standardized l Significance l Correlations Coefficients ! Zero Partial ___ ___ .137 .013 .282 .102 .171 .000 .290 .145 .002 .109 .337 .113 .963 .021 .211 .229 .002 .095 Regression coefficient significant at p>.OS, two tailed test. Next, in Table 4.31, for the older birth cohort in 1991-1998, we see that spouses' occupational prestige has stronger significance at .002, and variation in men's subjective class identity is more affected by spouses' occupational prestige, Beta coefficient .122. Finally, in Table 4.32, for the youngest birth cohort of men, 30-40 in 1991-1998, the significance of spouses' occupational prestige has reached .001, and the effect as shown by the Beta has increased slightly more to .130. 91

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Table 4.31 Correlation-Regression Analysis for the Relationship of Men's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 40 to 50 1991-1998 Standardized I Significance Correlations Independent Variables Coefficients I 1 Zero Partial I I ____ l _____________ _________ Men's Years of Education .291 .000 .439 .233 Men's Occupational Prestige .190 .000 .388 .173 Spouses' Years of Education Spouses' Occupational Prestige Multipler R2 -.004 .122 .482 .233 Regression coefficient significant at p>.OS, two tailed test. .921 .002 .298 .266 Table 4.32 Correlation-Regression Analysis for the Relationship of Men's and Spouses' Years of Education and Occupational Prestige to Subjective Class Identity Men 30 to 40 1991-1998 -.004 .117 Standardized I Significance I Correlations Independent Variables Coefficients I I Zero Partial I I ___ ____ j_ ____________ Men's Years of Education .206 .000 .405 .166 Men's Occupational Prestige .209 .000 .400 .180 Spouses' Years of Education Spouses' Occupational Prestige Multiple R R2 .044 .130 .469 .220 Regression coefficient significant at p>.OS, two tailed tes .327 .001 .320 .300 .037 .106 In Tables 4.30, 4.31 and 4.32, wives' occupational prestige becomes increasingly significant as the men become younger. The Beta weights show that spouses1 occupational prestige has an increasingly stronger effect on men1s subjective class identity. 92

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In sununary, this data show first, that the two birth cohorts have different perceptions of parental influence. We saw that the older women showed a preference for mothers' indicators and the younger women favored fathers indicators. There may be socio-economic attitudes of these women that explain this stronger identification with either mothers or fathers. Two possibilities are, 1) the older women because of the limited job opportunities identify more with mothers' occupational prestige and remain in jobs similar in prestige to their mothers and; 2) the younger cohort with better job opportunities identify more readily with fathers' and spouses' occupational prestige because they have had more access to jobs similar to their fathers' and spouses'. Without more data or further research, one can only speculate why there is a difference in the two birth cohorts of women. This data analysis shows that in recent years mothers' social status indicators of years of education and occupational prestige are having an effect on the years of education, occupational prestige, and subjective class identity of women; and as the influence of mothers' indicators has increased fathers influence has decreased. This study shows there is a continuing strong influence from spouses' social status indictors when women are measuring their social class. However, women have begun to measure their social status using their own social class 93

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indictors. This data analysis shows that women's years of education and occupational prestige are influenced by the years of education and occupational prestige of mothers. While mothers' years of education and occupational prestige do not have a strong influence when compared to spouses indictors, these data suggest that mothers influence probably comes prior to the influence of spouses social class indictors, and mothers influence almost certainly continues after marriage because of women's higher years of education and occupational prestige. The brief data analysis of men's subjective class identity shows that men have begun to measure their subjective class identity by including spouses' social class indictors. Though this change is slight, it is a shift from the long held traditional belief that women's indicators are not a part of the family social status equation. Data here indicate a trend with both American women and men of changing perceptions of what measures social class that begs inclusion in measurements of social stratification. 94

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CHAPTERS CONCLUSION There have been few developments in measurement of social stratification and gender in the last thirty years despite the cultural and economic changes for women that have taken place. Women's socio-economic advancement and achievement have not gone beyond being a postscript to the socio-economic position of men in stratification studies. Studies of social class are failing to add data about women's educational and occupational achievements as indictors for measuring family social position. Inquiry into social stratification should not ignore the intergenerational and intragenerational patterns of reproduction of social status. Erik Wright said that "Class Counts," I say that "Mother Matters" when determining the social class position of her children. To answer the question, "Do mothers' social status indicators influence women's social class?" this study compared mother's work history, years of education, and occupational prestige with women's work history, years of education, occupational prestige, and subjective class identity. Studies have found that indexes of occupational prestige give a reasonably accurate picture of social status. In the past, intergenerational studies of social 95

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status have proved accurate, but most studies on occupational mobility and prestige have focused on sons and fathers. The few studies done on daughters have also used fathers' social class indicators. Blau and Duncan's study (1967) showed that fathers' education and occupation had an affect on sons' education and occupation. Two other studies (DeJong, et al1971 and Tyree and Treas 1974) done shortly after Blau and Duncan looked at women's intergenerational occupational mobility but continued to use the father's occupation as the indicator of a daughters' occupational mobility. Mothers have a great deal of influence on their children. Studies of the socialization of children show conclusively that the mother is the primary socializing agent for her children. Tallecit and Willits suggested that it is not just mothers' educational attainment and work history that influences their daughters but also mothers' attitudes about work and education. (p. 225) Henderson said, "We know that the mother, in her everyday interactions with her child, continually functions as a teacher." (p. 148) It stands to reason then that a mother's educational attainment and occupational prestige would affect the education and occupation of her child and that employed mothers, especially those in high status occupations would encourage high achievement in their children. 96

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The conclusions reached here dispute the traditional method of measuring social status. The significant conclusions that can be interpreted from this study are, that in the last three decades, 1) Mothers have increased their influence on the occupational prestige and the subjective class identity of women; and fathers' influence has decreased, 2) Women are increasingly interpreting their social status through their own social class indicators. This challenges the accuracy and applicability of continued analysis of social stratification relying on data about the male head-of-household only. This study shows that the effects of mothers' working on daughters' education, occupation, and social class selection have grown stronger in the last thirty years. There are more women and more mothers in the labor force today than thirty years ago. In the 1970s, about 1 in 2 women who worked had mothers who worked while they were growing up. That number is now about 3 in 4. This study shows that, if a woman's mother worked while she was growing up, the woman herself was more likely to work. Even if we allow for the possibility of other issues influencing women's employment it is probable that women who work were influenced by having mothers who worked while they were growing up. This appears to have an effect on women's independent occupational prestige and subjective class identity, in that women would be more likely to enter and 97

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stay in the workforce affecting their intergenerational and intragenerational occupational mobility. This study also shows that mothers' years of education and occupational prestige have an influence on women's years of education, occupational prestige and subjective class identity. The more education mothers have the more education daughters have. The more years of education mothers have the higher daughters occupational prestige. The higher mothers' occupational prestige the higher daughters' occupational prestige. Because occupational prestige is an accepted measure of social status in social stratification studies, it seems obvious that mothers' educational attainment and occupational prestige is affecting their daughters' social position. The more years of education and the higher the occupational prestige, the higher women measure their class position. Even when we consider the influence of fathers and spouses, this trend of mothers' influence continues. Since this study explores the intergenerational influences on women's occupational prestige and subjective class identity, it was important to look at data on parents only. For both birth cohorts, when spouses' social class indictors are removed .from the regression analysis, mothers' occupational prestige is the most likely indictor to influence women's occupational prestige and subjective class identity. Fathers' years of education is the second influence; mother's years of education is third; and last is father's 98

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occupational prestige. That mother's social class indicators are affecting women's occupational prestige and subjective class identity effectively shows us that mothers social status indictors should probably be included in social stratification measurement. The data show that there are some differences between the older birth cohort and the younger birth cohort in their perception of intergenerational influences. As discussed earlier, this may be an effect of women's culturally socialized about gender equality, and in differences in the advantages of educational and occupational attainment available to the younger women. Even so, it has been shown here that the higher mothers' years of education and occupational prestige, the higher women's occupational prestige and subjective class identity, As expected from evidence in previous studies, in this study also, the one continuous influence found on women's social status is that of spouses. For both birth cohorts in the early and later years, spouses' indictors influence women's occupational prestige and subjective class identity. However, past studies (Baxter 1994, Simpson, et. al. 1988, Davis and Robinson 1988) have found that women who work are becoming more likely to decide their social class position independent of their spouses. This made it important to compare women's subjective class identity to her own occupational prestige as well as that of her 99

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mother, father, and spouse. For both birth cohorts, it is only fathers' occupational prestige that does not influence women's subjective class identity. For the older women, 40-50, mothers' occupational prestige is second only to spouses' in influencing subjective class identity. For the younger women 30-40, their own occupational prestige as well as their spouses' affects their subjective class identity. This study shows that women's own educational attainment and occupational prestige have become important when assessing their social status. It is also noted here that men are more readily including their wives' occupational prestige when determining family social position. If women are achieving similar patterns of occupational mobility as men, their social status should be measured by their occupation just as it is for men whether they are mani.ed or not. Although this presents a problem recognized by several sociologists (Acker 1980, Treiman and Terrell1975, Rosenfeld 1978, Davis and Robinson 1988), which is, how to measure social status of women who do not work for pay and cannot be categorized by their own occupation. Using social status indicators for mothers, such as years of education and occupational prestige, when measuring social position could help to ameliorate this difficulty. Continued research along these lines would be worth pursuing. 100

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Occupational prestige is an important part of social stratification study. With the majority of women now in the labor market, using the family unit/male head-of-household model to measure social position is no longer adequate. Women detennining their subjective class identity based on their own merit is an important shift for women in recent years and shows that the traditional method of male as head-of-household measurement of social position in social stratification studies should be reconsidered. This becomes an even more urgent issue when we see that even men's subjective class identity is being affected by years of education and occupational prestige of spouses. Various studies (Adams 1967, Kalmijn 1994, Tallecit and Willis 1986) show that mothers make a difference in attitudes of both their male and female children. For example, Adams found that, "The experience of upward mobility tends to be associated with a close relationship between both sexes and the mother .... If children have a close relationship with their mother, both males and females considered their mother to be the main influence on their upward mobility. (p. 370). Kalmijn found that the affect of mother's occupational status was just as strong for sons as it was for daughters (p. 272). Women are no longer completely willing to borrow their class identification from their husbands, and we found that husbands are no longer expecting them to. "When men and women identify with a class, they see 101

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themselves as belonging to it. Class identification expresses in a symbolic way their own experiences with power and privilege" (Simpson, et. al. 1988 p. 285). The empowerment that women have acquired through their work experience has become as important a part of class identification for women. As this study shows, men and women both are assuming a "sharing" model for identifying their subjective class identity. When we briefly compared data on men, we discovered that an important change in male perception of class identity is occwring. Wives occupational prestige is influencing husbands' social class selection. The trend towards husbands taking into account their spouses occupational prestige when deciding class position is an important shift and of major importance in the argument for inclusion of data on wives when determining a family's social status. As the findings here show, 1) Women's occupational prestige and subjective class identity are being influenced by their mothers, 2) Women's subjective class identity is being influenced not only by husbands' indicators, but also by their own social class indictors and; 3) Men's subjective class identity is being influenced not only by their own social class indicators but also by those of their wives. It is not impossible to believe then, that women's mothers are having an indirect effect on men's subjective class identity and subsequently on family social status. "Mothers matter" and perhaps I should add, "mothers-in-law 102

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matter." Future studies in social stratification should consider the effects of mothers on their children's family social status. Admittedly, multiple methods of analysis using different variables to measure stratification depending upon the problem being studied may be needed. Using variables on mother's educational attainment and occupational prestige could be a method of measuring social stratification that would affect the accuracy of social status. This study shows a pattern of change since the 1970s in women's and men's individual perception of what measures social class. As Blau and Duncan suggested in their 1967 study, ... any difference large enough to be interesting is statistically significant" (p. 17). This study shows that women have a new awareness of their contribution to family social class and mothers' social status characteristics influence the social status characteristics of daughters.By knowing mothers' social class indicators, one can predict with reasonable accuracy the social class of daughters. Though slight, the degree of change that mothers are making in their daughters' educational attainment, occupational prestige, and subjective class identity are significant enough to expect that the change will become even more important in the future. These results suggest that there should be renewed interest in developing a more current model for measuring social stratification. The use of women's own social class indictors and intergenerational characteristics, 103

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especially those of the mother, can enhance the body of information in social stratification research and increase the validity of data. My fmdings support the need for continued research into how "mothers matter" in social stratification. 104

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APPENDIX A CHAPTER 4 DATA ANALYSIS: COMPLETE TABLES AND DATA Table 4.la-All Respondents' Work History OSS YEAR FOR THIS RESPONDENT worll: sb1tw of re&pOrdllnt C routlllbulatlon -WI:A'iting Cl' ....... havawm"ked T""" GSSYEAR 1972 eo..,t 428 347 775 FOR THIS % within OSS YEAR FOR 65.2% 44.SO..L 100.0% RESPONDENT THIS RESPONDENT 1973 Count 419 357 776 %within GSS YEAR FOR 54.0% -46.0% 101).0% THIS RESPONDENT 1974 Count 412 358 770 % wt\J'in OSS YEAR FOR 63.5% 46.6% 100.0% THIS RESPONDENT 1975 Cowrt ... 397 792 % within GSS YEAR FOR 49.9% 60.1% 100.00tL THIS RESPONDENT 1976 """" 425 358 811 % 'Nittin GSS YEAR FOR 52.4% 47.6% 100.0% THIS RESPONDENT 1977 Count 354 459 813 % wlttin GSS YEAR FOR 43.5% 56.5% 100.0% THIS RESPONDENT 1978 eo..rt 374 474 848 % wilti'n ClSS YEAR FOR 44.1% 55.9% 100.0% THIS RESPONDENT 1980 c,..,. 349 442 791 % within GSS YEAR FOR 44.1% 55.9% 100.0% THIS RESPONDENT 1982 c"'"" 395 635 1000 %wfthinGSSYEAR FOR 38.3% 61.7% 100.0% THIS RESPONDENT 1983 """" 337 633 870 %within GSS YEAR FOR 38.7% 61.3% 100.0% THIS RESPONDENT 1984 Count 292 556 848 % wil:hin GSS YEAR FOR 34.-4% 65.6% 100.0% THIS RESPONDENT 1985 c .... 268 548 816 %VwilhinOSSYEAR FOR 32.8% 67.2% 100.0% THIS RESPONDENT 1986 c .... 300 515 816 % wittin OSS YEAR FOR 36.8% 63.2% 100.0% THIS RESPONDENT 1987 c..., 286 704 !190 %within OSS YEAR FOR 28.9% 71.1% 100.0% ll'IIS RESPONDENT 1988 Counl 225 6T6 801 %within GSS YEAR FOR 28.1% 71.9"..1! 100.0% THIS RESPONDENT 1989 Count 263 6T1 834 %within GSS YEAR FOR 31.6% 68.6% 100.0% THIS RESPONDENT 1990 Count 183 638 731 % wi'lhin ass YEAR FOR 26.4% 73.6% 100.0% THIS RESPONDENT 1991 Count 263 563 846 % wi1hin GSS YEAR FOR 31.1% ... .,. 100.0% THIS RESPONDENT 1993 Count 210 659 869 % within ass YEAR FOR 2-4.2% 7S.8% 100.00k THIS RESPONDENT 1994 Count 376 1260 1635 %within ass YEAR FOR 22.9% n.1% 100.0% THIS RESPONDENT 1996 Count 323 1208 1531 %within GSS YEAR FOR 21.1% 76.9% 100.0"M THIS RESPONDENT 1998 Count 312 1212 1624 % within GSS YEAR FOR 20.5% 79.5% 100.0% THIS RESPONDENT Tol8l Counl 7198 13318 20516 % within GSS YEAR FOR 36.1% 64.9% 100.0% THIS RESPONDENT 105

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Table 4.1b-All Respondents' Mothers' Work History While Respondent Was Growing up GSS YEAR FOR THIS RESPONDENT was mother 9111ployed while was growing up Crosstabulstlon was mather employed while respondent was up no ,.,, 357 % within GSS YEAR FOR RESPONDENT "THIS RESPOIIDENT 51.9% 1974 COunt 347 % within GSS YEAR FOR 50.1% "THIS RESPONDENT 1975 Count 354 % wi1hln GSS YEAR FOR 4B.3% THIS RESPONDENT 1976 COunt 370 % within GSS YEAR FOR 51.1% "THIS RESPONDENT 1an COunt 379 % within GSS YEAR FOR 52.3% "THIS RESPOII!JENT 1978 Count 348 % within GSS YEAR FOR 44.5% "THIS RESPOIIDENT 1980 Co urn 325 % wi1hln GSS YEAR FOR 44.0% "THIS RESPOII!JENT 1982. COunt 404 % within GSS YEAR FOR 45.2% "THIS RESPONDENT 1983 Count 326 % within GSS YEAR FOR 40.0% "THIS RESPONDENT 1984 Courrt 287 % wi1hln GSS YEAR FOR 36.8% "THIS RESPOIIDENT 1985 COunt 300 % within GSS YEAR FOR 40.7% "THIS RESPOIIDENT 1986 Count 292 % within GSS YEAR FOR 38.3% "THIS RESPONDENT 1987 COunt 324 % within GSS YEAR FOR 36.4% "THIS RESPONDENT 1988 COunt 263 % wi1hln GSS YEAR FOR 35.2% "THIS RESPOIIDENT 1989 COunt 304 % within GSS YEAR FOR 39.0% "THIS RESPOIIDENT 1990 COunt 246 % within GSS YEAR FOR 35.9o/o "THIS RESPONDENT 1991 COunt 269 % within GSS YEAR FOR 34.9% "THIS RESPONDENT 1993 Count 250 % wi1hln GSS YEAR FOR 31.8% "THIS RESPONDENT 1994 Count 645 % within GSS YEAR FOR 40.6% "THIS RESPOIIDENT 1996 COunt 548 % within GSS YEAR FOR 35.6% "THIS RESPOIIDENT 1998 COunt 558 % within GSS YEAR FOR 37.7% "THIS RESPONDENT To1SI COunt 7496 % within GSS YEAR FOR 40.9% "THIS RESPONDENT 106 yes Total 331 688 48.1% 100.0% 345 692 49.9% 100.0% 379 733 51.7% 100.0% 354 724 48.9% 100.0% 346 725 47.7% 100.0% 434 782 55..5% 100.0% 413 738 Sti.O% 100.0% 489 893 54.8% 100.0% 489 815 60.0% 100.0% 492 779 63.2% 100.0% 438 738 59.3% 100.0% 471 763 61.7% 100.0% 567 891 63.6% 100.0% 485 748 64.8% 100.0% 475 n9 61.0% 100.0% 439 885 64.1%. 100.0% 501 no 65.1% 100.0% 537 787 68.2'/o 100.0% 943 1588 59.4% 100.0% 990 1538 64.4% 100.0% 923 1481 62.3% 100.0% 10841 111337 59.1% 100.0%

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Table 4.2a-1972-1978, Work Status ofWomen 40-50 and Mothers' Work History was mother employed v.1111e respondent was growing up work status of respondent women 40 -50 yeaJS old Crosstab.lladon work stab.Js of respondent keeping working or women 40 -50 jlears old house have worked age40-50 was mother employed no Count 161 210 while respondentwas %within work st:a1J.Js 52.8% 50.4% growing up of respondent yes Count 144 207 %within work status 472% 49.6% of respondent Total Count 305 417 %within work status 100.0% 100.0% of respondent Total 371 51.4% 351 48.6% 722 100.0% Table 4.2b-1972-1978, Work Status ofWomen 30-40 and Mothers' Work History was mother employed while respondent was growfng up ,. work status of respondent women 30 tD 40 years old Crosstallulation work status of respondent keeping working or women 30 tD 40 veers old house have worked age 30-40 .. no Count 195 162 %within work status 41.9% 32.7% growing up of respondent yes Count 270 334 % wilhin work status 58.1% 67.3% of respondent Total Count 465 496 % wilhin work stab.ls 100.0% 100D% Total 357 37.1% 604 62.9% 961 100.0% Table 4.2c-1991-1998, Work Status of Women 40-50 and Mothers' Work History was mother employed while respondent was growing up work status of respondent women 40 -50 years old Crosstallulation work status of respondent keeping working or women 40 -50 vears old house havewor1
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Table 4.3a-All Respondents' Years of Education RESPONDENT Total GSS YEAR FOR ntiS RESPONDENT ntspondent's yaars oloducauon In 3 COUigonas Crosstabulatlon respondents years of education in 3 cataaorles 2 97< QJunt 328 291 %within GSS YEAR FOR 40.7% 36.1% ntiS RESPONDENT 1973 Count 290 301 %within GSS YEAR FOR 36.3% 37.6% THIS RESPONDENT 1974 Count 252 315 %within GSS YEAR FOR 31.9% 39.8% THIS RESPONDENT 1975 Count 300 299 %within GSS YEAR FOR 36.7% 36.4% ntiS RESPONDENT 1976 Count 303 326 % wlthln GSS YEAR FOR 36.7% 39.5% THIS RESPONDENT 1977 Count 304 309 %within GSS YEAR FOR 36.6"/o 37.2% THIS RESPONDENT 1978 Count 299 331 %within GSS YEAR FOR 33.8% 37.4% THIS RESPONDENT 1990 Count 270 303 %within GSS YEAR FOR 32.8% 36.8% THIS RESPONDENT 1982 Count 363 371 %within GSS YEAR FOR 33.7% 34.5% THIS RESPONDENT 1993 Count 254 337 %within GSS YEAR FOR 27.9% 37.1% ntiS RESPONDENT 1984 Count 240 305 %within GSS YEAR FOR 27.5% 34.9% THIS RESPONDENT 1985 Count 232 301 %within GSS YEAR FOR 27.4% 35.6% THIS RESPONDENT 1986 Count 252 309 %Within GSS YEAR FOR 29.7% 36.4% THIS RESPONDENT 1997 Count 285 358 %within GSS YEAR FOR 27.6% 34.6% THIS RESPONDENT 1988 Count 229 275 %within GSS YEAR FOR 272% 32.7% THIS RESPONDENT 1989 Count 227 296 %within GSS YEAR FOR 26.0% 33.9% ntiS RESPONDENT 1990 Count 170 261 % wlthln GSS YEAR FOR 22.1% 34.0% THIS RESPONDENT 1991 Count 210 285 %within GSS YEAR FOR 23.9% 32.5% THIS RESPONDENT 1993 Count 181 293 %within GSS YEAR FOR 19.7% 31.9% THIS RESPONDENT 1994 Count 319 545 %within GSS YEAR FOR 19.7% 32.1% THIS RESPONDENT 1996 Count 2B8 490 %within GSS YEAR FOR 17.9% 30.4% THIS RESPONDENT 1998 Count 273 498 %within GSS YEAR FOR 17.1% 31.2% THIS RESPONDENT Count 5988 7398 %within GSS YEAR FOR 27.5% 34.7% THIS RESPONDENT 108 3 Total 186 805 23.1% 100.0% 209 800 26.1% 100.0% 225 792 28.4% 100.0% 220 819 26.9% 100.0% 196 825 23.8% 100.0% 217 830 26.1% 100.0% 255 995 28.9% 100.0% 250 823 30.4% 100.0% 342 1076 31.8% 100.0% 319 909 35.0% 100.0% 329 874 37.6% 100.0% 313 846 37.0% 100.0% 288 849 33.9% 100.0% 391 1034 37.8% 100.0% 337 841 40.1% 100.0% 350 873 40.1% 100.0% 337 788 43.9% 100.0% 392 877 43.6% 100.0% 445 919 48.4% 100.0% 936 1699 49.2% 100.0% 934 1812 51.7% 100.0% 924 1595 51.7% 100.0% 8084 21350 37.9% 100.0%

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Table 4.3b-All Respondents' Mothers' Years of Education GSS YEAR FOR THIS RESPONDENT nspondent's mother"& years of education Oosstabulatlan resnondenrs mather's vears of education not more than at least eleven years high school one year of school Qraduete Total 972 Count 399 141 72 612 %within GSS YEAR FOR RESPONJENT THIS RESPONJENT 65.2% 23.0% 11.6% 100.0% 1973 Count 374 189 71 634 % wHhln GSS YEAR FOR 59.0% 29.8% 11.2% 100.0% THIS RESPONJENT 1974 Count 407 174 90 671 % within GSS YEAR FOR 60.7% 25.9% 13.4% 100.0% THIS RESPONDENT 1975 Count 423 188 85 698 % within GSS YEAR FOR 60.8% 27.0% 12.2% 100.0% THIS RESPOI>IJENT 1976 Count 416 188 64 668 % within GSS YEAR FOR 62.3% 29.1% 9.6% 100.0% THIS RESPONJENT 1977 Count 396 194 73 663 % within GSS YEAR FOR 59.7% 29.3% 11.0% 100.0% THIS RESPONJENT 1978 Count 401 237 90 728 % within GSS YEAR FOR 55.1% 32.6% 12.4% 100.0o/t THIS RESPONJENT 1980 Count 384 195 108 687 % within GSS YEAR FOR 55.9% 28.4% 15.7% 100.0% THIS RESPONJENT 1982 Count 457 257 131 845 % within GSS YEAR FOR 54.1% 30.4% 15.5% 100.0% THIS RESPONJENT 1983 Count 385 263 132 780 % within GSS YEAR FOR 49.4% 33.7% 16.9% 100.0% THIS RESPONJENT 1984 Count 371 264 110 745 % wnhln GSS YEAR FOR 49.8% 35.4% 14.8% 100.0% THIS RESPONJENT 1985 Count 346 263 104 713 % wnhln GSS YEAR FOR 48.5% 36.9% THIS RESPONJENT 14.6% 100.0% 1986 Count 344 246 117 707 % within GSS YEAR FOR 48.7% 34.8% 16.5% 100.0% THIS RESPONJENT 1987 Count 435 269 161 865 % within GSS YEAR FOR 60.3% 31.1% 18.6% 100.0% THIS RESPONJENT 1988 Count 332 241 138 711 % within GSS YEAR FOR 46.7% 33.9% THIS RESPONJENT 19.4% 100.0% 1989 Count 371 238 149 758 % within GSS YEAR FOR 48.9% 31.4% 19.7% 100.0% THIS RESPONDENT 1990 Count 283 224 144 651 % within GSS YEAR FOR 43.6% 34.4% 22.1% 100.0% THIS RESPONJENT 1991 Count 320 2S1 141 722 % within GSS YEAR FOR 44.3% 36.1% 19.5% 100.0% THIS RESPONJENT 1993 Count 314 296 179 789 %within GSS YEAR FOR 39.8% 37.5% 22.7% 100.0% THIS RESPONDENT 1994 Count 571 522 344 1437 %within GSS YEAR FOR 39.7% 38.3% 23.9% 100.0% THIS RESPONDENT 199S Count 459 528 376 1363 % within GSS YEAR FOR 33.7% 38.7% THIS RESPOI>IJENT 27.6% 100.0% 1998 Count 486 602 363 1351 % within GSS YEAR FOR 38.0% 37.2% 26.9% 100.0% THIS RESPONJENT Total Count 8674 5880 3242 17796 o/a within GSS YEAR FOR 48.7% 33.0% 18.2% 100.0% THIS RESPONJENT 109

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Table 4.4a-1972-1978, Occupational Prestige Women 40-50 and Mothers' Years of Education respondents mother's years or education 3 catagortes of occupational preslfgHespondent women 40 -50 years old CrosstabulaHon 3 catagorfes of oa;upaUonal prastige-respo!ldent women 40 -oo veaJS old 1G-36 respondenrs not more than eleven count 267 mothe(s years of scllool %within 3 catagcrles years of or occupational 76.5% education prestige-respondent high scllool graduate Count 66 %within 3 catagorfes or oa;upational 16.9% prestige-respondent at least one yest: of Count 16 ooll-%within 3 catsgories or occupational 4.6% prestige-respondent Total Count 349 % within 3 catagories of occupational 100.0% prestige-respondent Table 4.4b-1972-1978, Occupational Prestige Women 30-40 and Mothers' Years of Education 37-Q 202 56.7% 96 27.0% 511 16.3% 356 100.0% 63-89 9 34.6% a 30.11%. 9 34.6% 26 100.0% responderrfs mother"& years of education 3 ca1agorles of occupaUonal prestige-respondent women 30 to 40 years old Crosstlbulatlon 3 catagorfes of oa:upational orestiae-resoondent women 30 to 40 years old 10.36 37-Q 63-89 ageJIHI.l responden s not more tnan e even UJUnt 307 214 9 mother's years of school % wl1hln 3 catagorles years of or occupational 67.9o/o 42.5% 32.1'% education prestige-respondent high scllool graduate Count 117 204 II % wilhln 3 catagories ol occupational 25.9% 40.6% 28.6% prestige-respondent at least one year of Count 211 115 11 collage %within 3 catagories or OCD.Jpational 62% 16.9% 39.3% prestige-respondent Total Count 452 503 211 % wiltlin 3 calagories of occupational 100.0% 100.0% 100.0% prestige-respondent Table 4.5a-1991-1998, Occupational Prestige Women 40-50 and Mothers' Years of Education respondent's mother"s years of education 3 catagortes of occupaUonal presUge--respondent women 40 -50 rears old Crosstabulatfon 3 catagorfes ol occupational presfioa-resoon< ant women 40 -oo years old 10.36 63-89 ageV respondenrs nol more than eleven o.;ount 190 2011 55 mother's years of scllool %within 3 c:alagorles years of of OCD.Jpational 49.0% 31.9% 24.9% education prestige-respordent high school graduate Count 150 21111 114 % within 3 catagories or oa;upational 38.7% 44.1% 38.0% presUge-resporxfent at least one year of Count 411 157 112 oollage % within 3 catagorfos of occopational 12.4% 24.0% 37.1% prestige-respondent Total Count 31111 653 221 % wllhln 3 catagorles of ocaJpationel 100.0% 100.0% 100.0% prestige-respondent 110 Total 476 65.4% 170 23.3% 113 11.4% 731 100.0% Total 530 53.9% 329 33.5% 124 12.6% 9113 100.0% Total 453 35.9% 522 41.4% 267 22.7% 1262 100.0%

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Table 4.5b-1991-1998, Occupational Prestige Women 30-40 and Mothers' Years of Education respondenfs mother's years of education 3 catagorln of occupational prestige-respondent women 30 to 40 years old CrosstalnllaUon 3 catagories of occupational Dl'8suae-resoondent women 30 ID 40 vears old 1()-36 37-62 8Q03\J-'IU responclenfs nol mone man eteven Counl 179 168 mo1l1e(s years or school % wilhln 3 catagories years of of occupational 34.3% 21.7"k education presUg.,...espondenl high school graduale Count 229 358 %within 3 catagories or occupational 43.9% 46.3% prestige--38 37-<12 1NU """"' 141 .., %wl1hln3catllga'les .. 72.3% 22.1% ,..._, 37-<12 Count 169 131 "' wil:tin 3 adlligo1M Ofc:ECUp!1ional <49.9% ...... --63-69 "'""" ,. 44 CIICIIICUP8Iicnlll 28.4% 431% --Tola! Cwnt 339 218 % wtthln 3 catagcrie.s "'63.3% 34.3% Table 4.6b-1994-1998, Occupational Prestige Women 30-40 and Mothers' Occupational Prestige WU'tlen 30 to -40 Yfllflnl dd 3 a.tagorhnt af ocalpld.lorml presUge-re..,ondent 3 cataQorkla of oocupatlonal pn.Uge-m other women 30 to 40 reeraold Croutabut.tlon ...._ .. -... -... ...... 1().313 37..(12 10.36 """" 156 104 %wi'lhln3cstagaiell .. __ 55.7% 37.1% JI'B!tig&-t"esp:lrdent 37-62 "'""" 174 198 % v.ithin 3 calagories .. 41.4% 47.1% ..... "'""" 38 .. ,._._ "'-32.2% 47.5'll> --c.unt 388 358 % witin 3 CWI!Pies QI(E(;upalionel 45.0% 43.8% 111 6:HI9 39 17.1% 92 40.4% 97 42.5% 228 100.0% ..... 11 ..... 39 11.5% ,. 28.4% 79 12.4% 63-$ 20 7.1% 48 11.o4% 24 20.3% ., 11.2% Total 366 25.3% 679 44.6% 459 30.1% 1524 100.0% To1BI 195 100.0% 339 100.0% 102 100.0% 636 100.0% T""" 280 100.0% 420 100.0% 118 100.0% 818 100.0%

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Table 4.7a-1994-1998, Occupational Prestige Women 40-50 and Mothers' Years of Education and Occupational Prestige Coefficients 11,b Stan dardi zed COeH UnstandardiZed icient Coefficients s 95% Confidence Interval for B COrrelations Model B Std. Error Beta t Sig. La.ver Bound Upper Bound Zero-order Partial 30.4J5 2.151 14.152 .000 26.211 34.656 .665 .211 .149 3.160 .002 .252 1.079 MOlliERS OCCUPA TIONA!. .197 .047 .197 4.169 .000 .104 .290 PRESTIGE (1960) a. Dependent Venable: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecling only cases for which WJmen 40 .SQ years old = age 40-50 Table 4.7b-1994-1998, Occupational Prestige Women 30-40 and Mothers' Years of Education and Occupational Prestige Coefficients -.b Stan dan:U zed COeH Unstandardized lcient COefficients s 95% Conrktence Interval fer B .262 .128 .263 .168 Correlations Model B Std. Error Beta t Slo. LoNer Bound Uooer Bound Zsro-order Partial (ICOnstant) 31.507 2.216 14.217 .000 27.156 35.857 MOMEO .525. .. . 206 .107 2.552 .011 .121 .929 MOlliERS OCCUPATIONAL .165 .042 .163 3.904 .000 .082 .248 PRESTIGE (1980) a. Dependent Variable: RS OCCUPATIONAL PRESTIGE SCORE (1960) b. Selecting only cases ror whldl women 30 to 40 years old "' age 3o-40 Table 4.8a-1994-1998, Subjective Class Identity Women 40-50 and Mothers' Years of Education and Occupational Prestige Coefficients 11,b Stan dardl zed COeH Unstandardized lcierrt Coefficients s 95% Confidence Interval for B .196 .092 .221 .139 Correlations Model B Std. Error Beta t Slg. Lower Bound Upper Bound zem..orcler Partial 1.798 .111 16.227 .000 1.580 2.015 .011 .165 3.664 .000 .021 .063 MOlliERS 4.408E-
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Table 4.9a-1994-1998, Subjective Class Identity Women 40-50 and Fathers' Years of Education and Occupational Prestige Coefficients .b Stan danil zed Coeff Unslllndartfozed I dent Coeflidents s 95% Confidence Interval for B Correia lions Model B Sid. Error Bets t Sia. Lower Bound Uocer Bound Zero-order Partial 1 =tent) 35.333 1.873 18.863 .000 31.656 39.011 .765 .152 .20S 5.024 .000 .466 1.064 FATHERS OCCUPATIONAL 7.04E.O:Z .046 .o63 1.515 .130 -.021 .162 a. Oependent Vartable: RS OCCUPA TIONA!. PRESTIGE SCORE (1980) b. Selecting only cases ror which 40 -so years okl "" age 40-50 Table 4.9b-1994-1998, Subjective Class Identity Women 30-40 and Fathers' Years of Education and Occupational Prestige Coafflctants a.b Stan dardl zed Coe" Unstsndan:lized iclent CoeffiCients s 95% Confidence lilte.rval fDr B .242 .1n .176 .054 Correlations Model B Std. Enor Bets I Sio. lower Bound UooerBound Zero-order Partial 1 31.492 1.666 .613 .140 .173 FATHERS OCCUPATIONAL .140 .039 .140 PRESTIGE SCORE (1980) e. Dependent Venable. RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 30 to 40 yeers old = age 3D-40 18.65tl .000 26.179 34.805 4.367 .000 .339 .887 3.559 .000 .063 .218 Table 4.10a-1994-1998, Subjective Class Identity Women 40-50 and Fathers' Years of Education and Occupational Prestige Stan dardl zed Coeff UnstBndardized lcient Coefficients s 95% Confidence Interval for B .251 .148 .237 .120 Correlations Model B Std. Enor Beta t Sig. Lcwer Bound Upper Bound Zero-order Partial 1 1.867 .089 21.079 .000 1.693 2.041 4.624E-02 .007 .259 6.446 .000 .032 .060 FATHERS OCCUPATIONAL 3.031E-OO .002 .055 1.384 .167 -.001 .007 a. Dependent Venable: respondents subjectrve class 1dentit)' b. Selecting only ca5e5 tor which women 40 -60 years okl = age 4o-50 Table 4.10b-1994-1998, Subjective Class Identity Women 30-40 and Fathers' Years of Education and Occupational Prestige Coeflh::lants ,b Stan dardl zed Coeff Unstendardlzed lcient Coefllclonts 95% Ccnfidence Interval for B .288 .222 .195 .049 Correlaflons Model B Std. Enor Bets t Sia. lo'Nel" Bound Uooer Bcund ZellHJrder Per11BI 1 1.915 .083 23.132 .000 1.752 2.on 3.579E-
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Table 4.11 a-1994-1998, Occupational Prestige Women 40-50 and Spouses' Years of Education and Occupational Prestige Coefflclants .b Stan dardl zed CoeR lJnstandard;zed lclent Coefficients s 95% Confidence Interval for B Correlations Model B Std. Entit Bela I Slg. Lower Bound UooerBound Zero-older 20241 2.701 7.494 .000 14.936 25.646 1290 225 270 5.733 .000 .848 1.732 SPOUSES OCCUPATIONAL .184 .046 .166 3.994 .000 .()94 275 PRESTIGE SCORE (1980) a. Deoendent Venable. RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 40 -50 years old = ege 4D-50 Table 4.11b-1994-1998 Occupational Prestige Women 30-40 and Spouses' Years of Education and Occupational Prestige Coefficients a.b Stan dardel B Std. Entit Beta I Slg. Lower Bound uooer Bound Zero-order 1 20.858 2.625 7.670 .000 15.504 25.812 1.087 .228 .206 4.669 .000 .618 1.515 SPOUSES OCCUPATIONAL .208 .044 .207 4.687 .000 .121 295 :71E980l a. Deoendent Vansble: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 30 to 40 years old = age 3G-40 Table 4.12a-1994-1998 Subjective Class Identity Women 40-50 and Spouses' Years of Education and Occupational Prestige Coefficients .,.. Stan dan:li Zed Co eft Unstanderdized lclent .328 .328 Pallial .176 .177 Coeffidents s 95% Confidence Interval for 8 Correbstkms Mxlel B Sid. Error Beta I Lower Bound UDDer Bound Zero-order 1 1.066 .121 8.621 .000 .1129 1.304 6.086E-02 .010 .380 7.978 .000 .061 .101 SPOUSES OCCUPA TIONA!. 7.947&03 .002 .170 3.773 .000 .004 .012 e. Dependent Variable: respondents subjective class Identity b. Selecring only cases for which v.ornen 40-50 years Old= ege 4o-50 Table 4.12b-1994-1998, Subjective Class Identity Women 30-40 and Spouses' Years of Education and Occupational Prestige Coefficients .b Stan dar
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Table 4.13-1994-1998, Occupational Prestige Women 40-50 and Mothers', Fathers' and Spouses' Years of Education and Occupational Prestige CoefficlentS'b Stan dardi zed Coeff Unstandardized icient Coefficients s S5% Confidence Interval for B Correlations Model B Std. Error Beta t SiQ. Lower Bound Uooer Bound Zero-order Partial Part 1 (Constant) 11.500 4.893 2.350 .020 1.863 21.137 MOM ED .516 .356 .111 1.449 .149 -.185 1.218 .292 .091 .082 MOTHERS OCCUPATIONAL .184 .074 .183 2.496 .013 .039 .330 .303 .156 .141 PRESTIGE (1980) PAED -.131 .277 -.034 -.471 .638 -.677 .415 .204 -.030 -.027 FATHERS OCCUPATIONAL 4.192E-02 .073 .038 .577 .565 -.101 .185 .187 .037 .033 PRESTIGE SCORE (1980) SPED 1.462 .356 .290 4.103 .000 .760 2.164 .373 .252 .232 SPOUSES OCCUPATIONAL 4.146E-02 .067 .043 .615 .539 -.091 .174 .252 .039 .035 PRESTIGE SCORE (1980) a. Dependent Variable: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 40 -50 years old = age 40-50 Table 4.14-1994-1998, Occupational Prestige Women 30-40 and Mothers', Fathers' and Spouses' Years ofEducation and Occupational Prestige CoefficientS'b Stan dardi zed Coeff Unstandardized lcient Coefficients s 95% Confidence Interval for B Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial Part 1 (Constant) 13.436 4.695 2.862 .005 4.198 22.674 MOM ED .374 .344 .073 1.086 .278 -.304 1.052 .234 .062 .057 MOTHERS OCCUPATIONAL 3.140E-02 .067 .031 .472 .638 -.100 .162 .225 .027 .025 PRESTIGE (1980) PAED .321 .276 .080 1.161 .246 -.223 .865 .288 .066 .061 FATHERS OCCUPATIONAL .146 .065 .143 2.250 .025 .018 .273 .299 .128 .117 PRESTIGE SCORE (1980) SPED .545 .344 .105 1.582 .115 -.133 1.222 .301 .090 .082 SPOUSES OCCUPATIONAL .175 .065 .172 2.690 .008 .047 .303 .308 .152 .140 PRESTIGE SCORE (1980) a. Dependent Variable: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 30 to 40 years old = age 30-40 115

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Table 4.15-1994-1998 Occupational Prestige Women 40-50 and Mothers' and Fathers' Years of Education and Occupational Prestige Coefficienttb Stan dardi zed Coeff Unstandardized icient Coefficients s % Confidence Interval for Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order 1 (Constant) 30.149 2.793 10.795 .000 24.661 35.637 MOMED .529 .260 .119 2.037 .042 .019 1.039 .250 MOTHERS OCCUPATIONAL .181 .054 .184 3.368 .001 .075 .286 .276 PRESTIGE (1980 PAED .214 .016 .263 .793 -.365 .478 .192 FATHERS OCCUPATIONAL .058 .058 1.096 .274 -.051 .178 .166 PRESTIGE SCORE (1980) a. Dependent Variable: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 40 -50 years old = age 40-50 Table 4.16-1994-1998, Occupational Prestige Women 30-40 and Mothers' and Fathers' Years of Education and Occupational Prestige Coefficientfb Stan dardi zed Coeff Unstandardized icient Partial .094 .155 .012 .051 Coefficients s 5% Confidence Interval for I Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 27.624 2.724 10.140 .000 22.273 32.976 MOM ED .119 .254 .025 .471 .638 -.379 .618 .196 .020 MOTHERS OCCUPATIONAL .106 .050 .105 2.115 .035 .008 .205 .209 .090 PRESTIGE (1980 PAED .494 .203 .130 2.429 .015 .095 .894 .253 .103 FATHERS OCCUPATIONAL .131 .051 .129 2.581 .010 .031 .231 .247 .110 PRESTIGE SCORE (1980) a. Dependent Variable: RS OCCUPATIONAL PRESTIGE SCORE (1980) b. Selecting only cases for which women 30 to 40 years old = age 30-40 116 Part .090 .149 .012 .049 Part .019 .086 .099 .105

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Table 4.17-1994-1998 Subjective Class Identity Women 40-50 and Mothers' and Fathers' Years of Education and Occupational Prestige Coefficientfib Stan dardi zed Coeff Unstandardized icient Coefficients s % Confidence Interval for Correlations Model B Std. Error Beta t Siq. ower Bounc Llooer Bound Izera-order Partial 1 (Constant) 1.557 .144 0.840 .000 1.275 1.839 MOM ED .634E-02 .013 .113 1.966 .050 .000 .053 .268 .090 MOTHERS OCCUPATIONA .626E-03 .003 .070 1.309 .191 -.002 .009 .227 .060 PRESTIGE (198 PAED .614E-02 .011 .191 3.259 .001 .014 .058 .300 .149 FATHERS OCCUPATIONA .642E-03 .003 .028 .544 .586 -.004 .008 .192 .025 PRESTIGE SCORE (1980) a. Dependent Variable: respondents subjec::tive class identity b. Selecting only cases for which women 40 -50 years old= age 40-50 Table 4.18-1994-1998 Subjective Class Identity Women 30-40 and Mothers' and Fathers' Years ofEducation and Occupational Prestige Coefficienftb Stan dardi zed Coeff Unstandardized icient Coefficients s % Confidence Interval for Correlations Model B Std. Error Beta t Sia. owerBounc l.Jooer Bounc Izera-order Partial 1 (Constant) 1.923 .125 5.400 .000 1.678 2.168 MOM ED .627E-02 .012 -.074 -1.386 .166 -.039 .007 .115 -.059 MOTHERS OCCUPATIONA .324E-03 .002 .136 2.724 .007 .002 .011 .181 .115 PRESTIGE (198 PAED .207E-02 .009 .184 3.390 .001 .013 .051 .226 .142 FATHERS OCCUPATIONA .498E-03 .002 .054 1.057 .291 -.002 .007 .178 .045 PRESTIGE SCORE (1980) a. Dependent Variable: respondents subjective class identity b. Selecting only cases for which women 30 to 40 years old = age 30-40 117 Part .086 .057 .142 .024 Part -.057 .111 .139 .043

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Table 4.19-1994-1998 Subjective Class Identity Women 40-50 and Mothers', Fathers', Spouses', and Women's Occupational Prestige Coefflclents"b Stan dardi zed Coeff Unstandardized icient Coefficients s 95% Confidence Interval for B Correlations Model B Std. Error Bela t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.048 .191 5.488 .000 .672 1.424 MOTHERS OCCUPATIONAL 9.282E.Q3 .003 .183 3.084 .002 .003 .015 .267 .185 PRESTIGE (1980) FATHERS OCCUPATIONAL 2.808E.Q3 .003 .050 .846 .399 -.004 .009 .216 .051 PRESTIGE SCORE (1980) SPOUSES OCCUPATIONAL 1.636E.Q2 .003 .339 6.002 .000 .011 .022 .396 .344 PRESTIGE SCORE (1980) RS OCCUPATIONAL PRESTIGE SCORE 5.8BOE.Q3 .003 .117 2.010 .045 .000 .012 .267 .122 (1980) a. Dependent Variable: respondents subjective class identity b. Selecting only cases for which women 40 -50 years old = age 40-50 Table 4.20-1994-1998 Subjective Class Identity Women 30-40 and Mothers' Fathers', Spouses', and Women's Occupational Prestige Coefflcients"b Stan dardi zed Coeff Unstandardized icient Coefficients s 95% Confidence Interval for B Correlations Model B Std. Error Bela t Sig. Lower Bound Upp_er Bound Zero-order Partial 1 (Constant) 1.347 .148 9.113 .000 1.056 1.638 MOTHERS OCCUPATIONAL 5.143E.Q3 .002 .113 2.097 .037 .000 .010 .229 .113 PRESTIGE (1980) FATHERS OCCUPATIONAL 5.321E.Q4 .002 .012 .214 .830 -.004 .005 .182 .012 PRESTIGE SCORE (1980) SPOUSES OCCUPATIONAL 1.319E.Q2 .002 .293 5.621 .000 .009 .018 .378 .292 PRESTIGE SCORE (1980) RS OCCUPATIONAL PRESTIGE SCORE 8.190E.Q3 .002 .187 3.544 .000 .004 .013 .303 .189 (1980) a. Dependent Variable: respondents subjective class identity b. Selecting only cases for which women 30 to 40 years old = age 30-40 118 Part .166 .045 .322 .108 Part .102 .010 .274 .173

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Table 4.21-1994-1998 Women 40-50 Subjective Class Identity and Women's, Mothers', Fathers', Spouses' Years of Education and Occupational Prestige Caefficlants11b Stan dardi zed Coell Unstandardized icient Coefficienls s 95% Confidence Interval for B Correlations Madel B Sid. Error Beta t Slg. Lower Bound Upper_ Bound Zero-order 1 .175 .245 .715 .475 -.307 .657 MOMED 4.028E-02 .017 .170 2.377 .018 .007 .074 .364 MOTHERS OCCUPATIONAL 8.557E-04 .004 .017 .243 .BOB -.006 .008 .267 PRESTIGE (1980) PAED 2.092E-02 .013 .108 1.606 .110 -.005 .047 .329 FATHERS OCCUPATIONAL -2.069E-03 .003 -.037 -.606 .545 -.009 .005 .204 PRESTIGE SCORE (1980) SPED 5.542E-02 .018 .217 3.060 .002 .020 .091 .461 SPOUSES OCCUPATIONAL 8.949E-{)3 .003 .184 2.819 .005 .003 .015 .412 PRESTIGE SCORE (1980) EDUCNEW 3.483E-{)2 .020 .128 1.742 .083 -.005 .074 .423 respondenls combined 1.012E-{)3 .003 .020 .309 .758 -.005 .007 .292 accupational prestige a. Dependent Variable: respondenls subjective class ldentil b. Selecting only cases lor which women 40 -50 years old = age 4D-50 Table 4.22-1994-1998 Women 30-40 Subjective Class Identity and Women's, Mothers', Fathers', Spouses' Years of Education and Occupational Prestige Coefficients.,., Stan dardi zed Caell Uns1Bndardized icient Partial .150 .015 .102 -.039 .191 .177 .110 .020 Coefficienls s 95% Confidence Interval far B Correladons Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) .993 .195 5.091 .000 .609 1.377 MOM ED -6.996E-03 .014 -.033 -.503 .615 -.034 .020 .136 -.029 MOTHERS OCCUPATIONAL 3.B53E-03 .003 .090 1.463 .145 -.001 .009 .207 .084 PRESTIGE (1980) PAED -2.498E-{)3 .011 -.015 -.228 .820 -.024 .019 .196 -.013 FATHERS OCCUPATIONAL -2.082E-{)3 .003 -.049 -.802 .423 -.007 .003 .162 -.046 PRESTIGE SCORE (1980) SPED 7.055E-02 .015 .326 4.695 .000 .041 .100 .464 .261 SPOUSES OCCUPATIONAL 6.0BOE-03 .003 .143 2.338 .020 .001 .011 .386 .133 PRESTIGE SCORE (1980) EDUCNEW 82B2E-03 .016 .036 .504 .615 -.024 .041 .346 .029 respandenls camblned 6.032E-03 .002 .144 2.488 .013 .001 .011 .298 .142 occupatianal prestige a. Dependent Vanable: respondenls subjective class ldentil b. Selecting only cases lor which women 30 ID 40 years old = age 3D-40 119 Pert .124 .013 .084 -.032 .160 .147 .091 .016 Pert -.025 .072 -.011 -.040 232 .115 .025 .123

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Table 4.23-1972-1978 Women 40-50 Subjective Class Identity and Women's and Spouses' Years of Education and Occupational Prestige Coefficien!S'b Stan dardi zed Coeff Unstandardized iclent Coefficients s 19s% Confidence Interval for B Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.581 .118 13.408 .000 1.350 1.813 EDUCNEW .171E .013 -.009 -.172 .864 -.027 .023 .231 -.007 respondents combined 3.364E-Q3 .002 .073 1.511 .131 -.001 .008 .239 .062 occupational prestige SPED 2.nsE-o2 .010 .151 2.909 .004 .009 .047 .336 .119 spouses occupational 1.187E-02 .002 .264 5.584 .000 .008 .016 .377 .223 prestige a. Dependent Variable: respondents subjective class identity b. Selecting only cases for which women 40 -50 years old = age 40-50 Table 4.24-1972-1978 Women 30-40 Subjective Class Identity and Women's and Spouses' Years of Education and Occupational Prestige Coefficients"b Stan dardi zed Coeff Unstandardized iclent Coefficients s 95% Confidence Interval for B Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.185 .109 10.841 .000 .971 1.400 EDUCNEW 2.656E-Q2 .012 .100 2.305 .021 .004 .049 .335 .081 respondents combined 1.796E-Q3 .002 .041 1.033 .302 -.002 .005 .267 .036 occupational prestige SPED 4.798E-Q2 .009 .241 5.395 .000 .031 .065 .412 .187 spouses occupational 7.110E-Q3 .002 .153 3.760 .000 .003 .011 .362 .131 prestige a. Dependent Variable: respondents subjective dess Identity b. Selecting only cases for which women 30 to 40 years old = age 3040 Table 4.25-1991-1998 Women 40-50 Subjective Class Identity and Women's and Spouses' Years of Education and Occupational Prestige Coefliclents"b Stan dardi zed Coeff Unstandardized icient Coefficients s 95% Confidence Interval for B Correlations Model B Std. Error Beta t SIQ. Lower Bound Uooer Bound Zero-order Partial 1 (Constant) .913 .116 7.863 .000 .685 1.141 EDUCNEW 3.469E-Q2 .010 .146 3.385 .001 .015 .055 .381 .123 respondents combined 2.469E-03 .002 .054 1.375 .170 -.001 .006 .291 .050 occupational prestige SPED 4.881E-Q2 .009 .231 5.449 .000 .031 .066 .436 .195 spouses occupational 8.327E-Q3 .002 .185 4.752 .000 .005 .012 .392 .171 prestige a. Dependent Variable: respondents subjective class Identity b. Selecting only cases for which women 40 -50 years old = age 40-50 120 Part -.006 .057 .109 .209 Part .073 .033 .170 .119 Part .107 .044 .173 .151

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Table 4.26-1991-1998 Women 30-40 Subjective Class Identity and Women's and Spouses' Years of Education and Occupational Prestige Stan dardl zed Coeff Unslandardized lclent Coefficients s 95% Confidence Interval for B Model B Std. Error Beta t Sla. Lower Bound Uooer Bound 1 (Conslant) .864 .108 7.968 .000 .651 1.076 EDUCNEW 3.650E-{)2 .010 .148 3.808 .000 .018 .055 respondents combined 5.452E.{)3 .002 .123 3.524 .000 .002 .008 occupational prestige SPED 4.727E.{)2 .009 .210 5.520 .000 .030 .064 spouses occupational 5.446E.{)3 .002 .121 3.407 .001 .002 .009 prestige a. Dependent Variable: respondents subjective class Identity b. Selecting only cases for which women 30 to 40 years old = age 30-40 Table 4.27-1994-1998 Subjective Class Identity Men 40-50 and Mothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige CoeHiclents .b Stan dardi zed Coelf Unslandardized ident Coellidents s 95% Confidence Interval lor B Model B Sid. Error Bela I Sig. lower Bound Upper Bound 1 1.315 .261 5.038 .000 .801 1.829 MAED -2.197E .017 -.102 -1275 204 -.056 .012 MOTHERS OCCUPATIONAL -3.069E.Q3 .003 -.072 -.988 .324 -.009 .003 PRESTIGE SCORE (1980) PAED 2.648E-Q2 .014 .161 1.940 .054 .000 .053 FATHERS OCCUPATIONAL 4.413E-03 .003 .102 1.361 .175 -.002 .011 PRESTIGE SCORE (1980) SPED -3.672E-Q2 .021 -.132 -1.785 .076 -.077 .004 SPOUSES OCCUPATIONAL 2.93BE.Q3 .003 .060 .921 .358 -.003 .009 PRESTIGE SCORE (1980) EDUC123 9.007E-02 .018 .404 4.902 .000 .054 .126 RS OCCUPATIONAL PRESTIGE SCORE 5.003E.Q3 .003 .118 1.591 .113 -.001 .011 (1980) a. Dependent V ar1able: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only cases 1tr which A GEGRUP1 = 1 121 Correlations Zero-order Partial .380 .123 .318 .114 .401 .176 .343 .110 Correlations Zero-order Partial .122 -.085 .098 -.066 .266 .129 .256 .091 .182 -.119 .122 .062 .460 .312 .371 .106 Part .109 .101 .158 .098 Part -.073 -.057 .112 .078 -.103 .053 282 .092

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Table 4.28-1994-1998 Subjective Class Identity Men 30-40 and Mothers', Fathers', Spouses', and Men's Years of Education and Occupational Prestige Coefficients a.b Stan dardi zed Coefl Unslandardized lcienl Coefficien1s s 95% Confidence Interval for 8 Model B Sid. Error Beta I Slo. lower Bound UDDer Bound 1 (Cons !ant) 1.177 .232 5.073 .000 .720 1.633 MAED -1.879E-Q2 .017 -.082 -1.086 .'ZT9 -.053 .015 MOTHERS OCCUPATIONAL 2.317E-Q4 .003 .005 .080 .936 -.005 .006 PRESTIGE SCORE (1980) PAED 3.744E-o2 .013 .2Z1 2.827 .005 .011 .064 FATHERS OCCUPATIONAL -4.322E-Q4 .003 -.010 -.147 .1183 -.006 .005 PRESTIGE SCORE (1980) SPED 9.031E-o3 .018 .038 .505 .614 -.026 .044 SPOUSES OCCUPATIONAL 8.051E-03 .003 .199 3.023 .003 .003 .013 PRESTIGE SCORE (1980) HIGHEST YEAR OF 3293E-o2 .019 .142 .080 -.004 .070 SCHOOL COMPLETED RS OCCUPATONAL 3.906E-03 .003 .094 1.313 .190 -.002 .010 PRESTIGE a. Dependent Variable: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only cases for which A GEGRUP2 = 2 Correlations Zero-order Partial .190 -.067 .153 .005 .339 .173 214 -.009 .318 .031 .311 .185 .359 .109 .318 .081 Table 4.29-1972-1978 Men 40-50 Subjective Class Identity and Men's and Spouses' Years of Education and Occupational Prestige Coafllclentll'b Stan dardi zed Coeff Unstandardlzed icient Coefficients s 5% Confidence Interval for I Correlations Model B Std. Error Beta I Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.308 .135 9.674 .000 1.043 1.574 EDUC123 .011 .184 3.298 .001 .015 .058 .383 .138 RS OCCUPATONA .003 .205 3.940 .000 .005 .015 .380 .165 PRESTIGE SPED .015 .067 1.282 .200 -.010 .047 .289 .054 SPRESALL .002 .063 1.279 .201 -.002 .008 .269 .054 a. Dependent Variable: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only cases for which AGEGRUP1 = 1 122 Part -.060 .004 .156 -.008 .028 .166 .097 .072 Part .126 .151 .049 .049

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Table 4.30-1972-1978 Men 30-40 Subjective Class Identity and Men's and Spouses' Years ofEducation and Occupational Prestige CoefficlentS'b Sten dardi zed Coelf Unstandardized icient Coefficients s 5% Confidence Interval for B Conelations Model B Std. Error Beta t Slg. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.508 .147 10.263 .000 1.219 1.796 EDUC123 3.003E-02 .012 .137 2.493 .013 .006 .054 .282 .102 RS OCCUPATONAL 8.646E-03 .002 .171 3.572 .000 .004 .013 .290 .145 PRESTIGE SPED 6.916E-04 .015 .002 .046 .963 -.029 .030 .211 .002 SPRESALL 5.459E-03 .002 .109 2.313 .021 .001 .010 .229 .095 a. Dependant Variable: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only cases for which AGEGRUP2 = 2 Table 4.31-1991-1998 Men 40-50 Subjective Class Identity and Men's and Spouses' Years of Education and Occupational Prestige CoefflclentS'b Stan dardi zed Coelf Unstandardlzed iclent Coefficienls s Confidence Interval for B Correlations Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Partial 1 (Constant) 1.092 .122 8.932 .000 .852 1.333 EDUC123 6.086E-02 .010 .291 6.348 .000 .042 .080 .439 .233 RS OCCUPATONAL 8.340E-03 .002 .190 4.665 .000 .005 .012 .388 .173 PRESTIGE SPED -1.107E-03 .011 -.004 -.099 .921 -.023 .021 .298 -.004 SPRESALL 5.636E-03 .002 .122 3.129 .002 .002 .009 .266 .117 a. Dependant Variable: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only casas for which AGEGRUP1 = 1 Table 4.32-1991-1998 Men 30-'40 Subjective Class Identity and Men's and Spouses' Years of Education and Occupational Prestige CoafficiantS'b Stan dardi zad Coalf Unstandardized icient Coefficients s 95% Confidence Interval for B Conelations Model B Std. Error Beta t Si!l. Lower Bound UDDarBound Zero-order Partial 1 (Constant) .982 .133 7.388 .000 .721 1.243 EDUC123 4.881E-02 .011 .206 4.489 .000 .027 .070 .405 .166 RS OCCUPATONAL 9.577E-03 .002 .209 4.865 .000 .006 .013 .400 .180 PRESTIGE SPED 1.151E-02 .012 .044 .980 .327 -.012 .035 .320 .037 SPRESALL 5.895E-03 .002 .130 3.199 .001 .002 .010 .300 .119 a. Dependent Variable: SUBJECTIVE CLASS IDENTIFICATION b. Selecting only casas for which AGEGRUP2 = 2 123 Part .096 .138 .002 .090 Part .210 .154 -.003 .103 Part .149 .162 .033 .106

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