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THESIS

 

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dissertation entitled

TESTING AN ECOLOGICAL MODEL OF CAREER ASPIRATIONS:
THE ROLE OF COMMUNITY, FAMILY, AND INDIVIDUAL HUMAN
CAPITAL VARIABLES AMONG PRE- AND MID-ADOLESCENT CHILDREN
OF PUBLIC ASSISTANCE RECIPIENTS

presented by

MELISSA SUE HUBER

has been accepted towards fulfillment
of the requirements for

Ph . D . degree in Psychology

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TESTING AN ECOLOGICAL MODEL OF CAREER ASPIRATIONS: THE ROLE OF
COMMUNITY, FAMILY, AND INDIVIDUAL HUMAN CAPITAL VARIABLES
AMONG PRE- AND MID-ADOLESCENT CHILDREN OF PUBLIC ASSISTANCE
RECIPIENTS

By

Melissa Sue Huber

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Psychology _

2000

ABSTRACT
TESTING AN ECOLOGICAL MODEL OF CAREER ASPIRATIONS: THE ROLE OF
COMMUNITY, FAMILY, AND INDIVIDUAL HUMAN CAPITAL VARIABLES
AMONG PRE- AND MID-ADOLESCENT CHILDREN OF PUBLIC ASSISTANCE
RECIPIENTS
By

Melissa Sue Huber

Because of the long term economic importance of career decisions made during
childhood and adolescence, this study examined community, mother, and child human
capital predictors of the socioeconomic status (SES) of the jobs desired and expected by 9-
13 year Old children (N=159) whose mothers were receiving public assistance. Human
capital was measured as the quality of jobs held by mothers and members of their
communities and was also measured by the educational attainments of the children,
mothers, and community members. For mothers and children, psychological self-
competence was also included as a measure of human capital. Using the ecological
framework it was hypothesized that the capital would flow from the commmtity to the
mother and then to the child. A path model was used to test this model which was
modified based on model-fitting exercises. Overall, the predicted ecological model was
supported in the final model. Community educational attainment predicted mother’s
educational attainment, which in turn predicted academic achievement and self-competence
of children. Children’s grades and the SES of mother’s jobs predicted children’s desired

and expected jobs and were the strongest influences of children’s career aspirations.

Demographic comparisons of job desires and expectations revealed no age
differences. However, females had higher desired and expected careers than males, and
children of White mothers had higher career expectations than children of Black mothers.
The SES Of children’s desired and expected careers were similar to each other and
remained stable from the first interview to the follow-up interview one year later.
However, the SES of children’s career aspirations were nearly twice that of their mothers
or their communities, unlike other studies of non-impoverished children whose career
aspirations were similar to their parents. This suggests that children living in poverty may
be less likely to realize their aspirations that other children. Although this model does not
explain how much socialization or accesses to Opportunities explain the impact of
community, mother, and child capital on children’s career decisions, it does indicate that
each is important in the broad picture of children’s career aspirations. Results suggest that

an ecological approach is needed to improve the career outcomes for children living in

poverty.

Dedication
Sociologist Linda Burton has been noted that it takes three generations to lay the
foundation for the career outcomes of children. In this study of children’s career
development I heartily acknowledge that I owe much Of my own career achievements to
the enduring support, influence, and hard work of my parents, grandparents, and great

grandparents who have meant so much in my life.

This manuscript is dedicated in their honor as a Shared achievement.
Jan and Rick Huber
Phyllis and Abe Roth Joann and Mel Huber
Rosa (Rensberger) Cleota (Gardner) Joella (Mishler) and Sarah (Shidler) and

and Ira Bechtel and Rollin Roth Ellis Detwiler George Huber

iv

Acknowledgements

Many people have helped me to complete this task and supported me in my
endeavors. Their many contributions are acknowledged here.

In addition to the support I have received from my parents and grandparents in
achieving my life goals, I also acknowledge the constant source of support and friendship
of my brothers, Robb and Nate, and my sister-in-law Kristin, and my Sousley family that
have helped me to persevere through the years.

I also wish to acknowledge my many friends who have shared in my dissertation
experience and have made my graduate school experience so memorable and all that I
could have ever wished it could be. These were times we have all shared together will
always be among the most special days I remember from MSU.

I thank my core MSU family of friends that formed a wonderful network of
support and friendship: Amber Lee Mushinske and Sara Joy Brink Ricks have been like
sisters to me and have created indelible memories of shared experiences that will always
bring me joy. I also thank our friends Steve Horstrnan, Kavi Maddula, Jeff Gray, Doug
Lynott, F aron Supanich-Goldner and many other members of our “potluck club” who spent
hours of fun fellowshipping over great meals and community volunteer activities. I
especially acknowledge the constant support I have received from one of our friends, Sam
Quon, who has become the greatest love of my life.

I also thank my MSU friends Bianca Guzman, who has inspired me to persevere
and keep my goals in front of me, as well as Domini Castellino and Dana Mastro for their
tremendous help in compiling data. I gratefully acknowledge the support of my colleagues

and the stafi' at the MSU Community Economic Development Program who have taught

me so much about successful community collaborations and have shared in my life over the
past few years. I also thank my student colleagues at the MSU Community/Ecological
Psychology Program who have liberally shared their resources with each another in such a
way as to make individual accomplishments possible.

In addition to my MSU friends, I have received valuable guidance and instruction
from many past and present MSU faculty and staff members that I also wish to thank.
LaRue Allen was instrumental and empowering in honing my youth development research
questions and helping me adjust to graduate school life. Annette Abrams, John Melcher,
and Rex LaMore have been stellar mentors in teaching me about applied policy analysis,
research, and outreach. Doug Luke provided in-depth mentoring in various research
methods and, in the process, shared general career wisdom and profound enthusiasm that
provided much needed inspiration. Bill Davidson and Tom Reischl provided helpful
reflection and guidance in many aspects of my graduate school education and my
socialization into the field of community psychology. Jackie Lerner also provided
incredible inspiration and support of my youth development interests and her scholarship in
this area contributed significantly to my understanding of this field.

I have particularly appreciated Peg Barratt’s insightful reflection and feedback in
the development of this study that has been strengthened by her vast understanding and
scholarship in the field of child development. I also acknowledge Pennie Foster-
Fishman’s help in providing in—depth feedback on this study as well as others, which has
helped me to become a better writer. I particularly thank Ralph Levine for his unremitting
kindness and gentleness in guiding this dissertation process. Such positive interactions

made the completion of this project possible. I also gratefully acknowledge the support of

Ellen Ernst Kossek who provided many hours of mentoring and support. She has taught me
much about the unfamiliar world of the academy and also provided invaluable access to the
important life stories of the mothers and children in this study that also made this project
possible.

Lastly, I wish to acknowledge the many mothers and children who shared their time
and their trust in telling us their stories in the hopes that their voices could be heard and

they could help to make the world a better place.

Table of Contents

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LIST OF TABLES X
LIST OF FIGURES XI
CHAPTER I INTRODUCTION AND OVERVIEW 1
OVERVIEW OF THE PRESENT STUDY -- . ................................................ 1
OUTLINE OF THE DISSERTATION _- . . ..... _ 2
SOCIAL SIGNIFICANCE OF THE PRESENT STUDY - 3
LIMITATIONS IN EXISTING LITERATURE IO
PURPOSE OF THIS STUDY .............. 12
CONTRIBUTIONS OF THIS RESEARCH 13
CHAPTER 2 LITERATURE REVIEW 15
IMPORTANCE OF CAREER DEVELOPMENT IN EARLY AND MIDDLE ADOLESCENCE ....... 15
THEORIES OF PERSON m CONTEXT HISTORY -- 16
AN ECOLOGICAL FRAMEWORK 21
NESTED SYSTEMS: A SPECIFIC ECOLOGICAL APPROACH 22
REVIEme CAREER ASPIRAIION LITERATURE PROM AN ECOLOGICAL PERSPECTIVE ................... 23
METHODS FOR SUMMARIZING LITERATURE ....... 26
INFLUENCE OF CHILD INDIVIDUAL DIFFERENCES ON CAREER ASPIRATTONS 26
FAMILY INFLUENCES ON CHILDREN’S CAREER ASPIRATTONS 43
COMMUNITY INFLUENCES ON CHILDREN’S CAREER ASPIRATTONS _ - - 59
SUMMARY OF EXPECTED EFFECT SIZES - - 68
CHAPTER 3 MODEL AND HYPOTHESES 71
RESEARCH FOCUS 71
OVERVIEW OF THE RESEARCH MODEL 72
HYPOTHESES AND PLANNED ANALYSES 72
USEFULNESS OF A PATH MODELING APPROACH TN TESTING COMPEITNG THEORIES ...................... 75
JUSTIFICATION FOR HYPOTHESES FOR HUMAN CAPITAL TRANSMISSION ACROSS ECOLOGICAL
LEVELS 76
JUSTIFICATION FOR LINKS wnHIN THE MEASUREMENT MODEL 80
INDIVIDUAL INFLUENCES -. 80
FAMILY (MATERNAL) INFLUENCES 82
COMMUNITY HUMAN CAPITAL PREDICTS MOTHER HUMAN CAPITAL ....... - 86
COMPARISONS BY CHILD DEMOGRAPHICS 87
CHAPTER 4 METHOD 89
PROCEDURES 89
SAMPIE 90
COMPARING THE SURVEY SAMPLE OF MOTHERS To THE RANDOM SAMPLE OF MOTHERS ................ 92
MEASURES ............ 93
CHAPTER 5 RESULTS 103
PROPOSED STRUCTURAL EQUATION MODEL . 106
FINAL STRUCTURAL EQUATION MODEL -- -106
GOODNESS OF FIT AND POWER OF THE FINAL STRUCTURAL EQUATION MODEL 1 10
COMMUNITY CAPITAL INFLUENCES ON MOTHER CAPITAL 1 1 1
MOTHER CAPITAL INFLUENCES ON CHILDREN 1 12
CHILDREN’S RESOURCES INFLUENCING CAREER ASPIRATTONS .......................... I I4
POST-HOC ANALYSIS OF MATERNAL EMPLOYMENT ON CHILD ASPIRATTONS 121
POST-Hoe COMPARISONS OF CAREER ASPIRATTONS OVER TIME - - 121
POST-HOC ASSESSMENT OF THE PERMANENCY OF MOTHER’S RESIDENCE ................................... 122
SUMMARY ....... 124
CHAPTER 6 DISCUSSION 125

 

COMPARING CAREER ASPIRATTONS OF STUDY CHILDREN TO EXISTING LITERATURE .................. 125

 

 

 

 

 

 

 

 

USEFULNESS OF ECOLOGICAL MODEL IN UNDERSTANDING CAREER ASPIRATTONS ..................... 127
COMPARISON OF MULTTVARIATE RESULTS To UNIVARIATE META-ANALYSIS RESULTS ............. 129
REAUTYANDTHERESIIJENCE OF CHILDREN LIVINGINPOVERTY -. 130
STUDY LIMITATIONS ...................................... 133
IMPLICATIONS FOR PRACTICE ......................................................................................................... 134
FUTURE RESEARCH ......................................................................... 136
LIST OF REFERENCES 138
APPENDICES 154
APPENDIX A — CHILD SELF-PERCEPTION PROFILE SURVEY QUESTIONS ....................................... 155
APPENDIX B — MOTHER SELF-PERCEPTION PROFILE SURVEY QUESTIONS .. 160
APPENDD( C - CHILDREN’S DESIRED AND EXPECTED CAREERS AT TIME 1 - 163
APPENDD( D -— CHILDREN’S DESIRED AND EXPECTED CAREERS TIME 2 171

APPENDIX E - PRESTIGE SCORES OF MOTHER’S CURRENT/MOST RECENT JOBS AT TIME 1 ........ 179
APPENDD( F - CONFIRMATORY FACTORY ANALYSIS RESULTS FOR HARTER CHILD SELF-

 

 

 

PERCEPTION PROFILE - 185
APPENDIX C — EXPLORATORY FACTORY ANALYSIS RESULTS FOR HARTER CHILD SELF-
PERCEPTION PROFILE 187
APPENDIX H - CONFIRMATORY FACTORY ANALYSIS RESULTS FOR HARTER ADULT SELF-
PERCEPTION PROFILE I 90
APPENDD( I — EXPLORATORY FACTORY ANALYSIS RESULTS FOR HARTER ADULT SELF-
PERCEP'TION PROFILE I92

 

List of Tables

 

 

TABLE 1 PERCENT OF CHILDREN EMPLOYED IN THEIR DESIRED CAREER (TRICE & McCLELLAN, I993) .............. 5
TABLE 2 EFFECTS OF ACADEMIC ACHIEVEMENT ON CAREER ASPIRATTONS ....................................................... 28
TABLE 3 EFFECTS OF SELF-ESTEEM ON CAREER ASPIRATTONS ........................................................................... 3 I
TABLE 4 EFFECTS OF AGE ON CAREER ASPIRATTONS ................. - ....................... 34
TABLE 5 EFFECTS OF GENDER ON EDUCATION LEVEL REQUIRED FOR DESIRED CAREER .................................. 39
TABLE 6 EFFECTS OF GENDER ON STATUS OR PRESTIGE OF DESIRED CAREER ................................................... 40
TABLE 7 EFFECT OF RACE ON CAREER ASPIRATTONS ....... - ....................... 45

 

TABLE 8 EFFECTS OF PARENT EDUCATION ON CHILD CAREER ASPIRATTONS AND EDUCATIONAL PLANS ......... 50

 

 

 

 

 

TABLE 9 STMILARITY BETWEEN PARENT JOBS AND CHILD CAREER ASPIRATTONS 52
TABLE 10 EFFECT OF PARENTS’ JOB/SOCIOECONOMIC STATUS ON CHILD CAREER ASPIRATTONS ..................... 55
TABLE 1 1 EFFECT OF COMMUNITY TYPE ON CAREER ASPIRATTONS .- 65
TABLE 12 EFFECTS OF COMMUNITY ECONOMIC OPPORTUNITIES ON CHILD CAREER ASPIRATTONS .................. 67
TABLE 13 META-ANALYSIS OF HUMAN CAPITAL PREDICTORS OF CAREER ASPIRATTONS ..................................... 70
TABLE 14 CLIENT CONSENT RATES IN THE FIRST INrERVIEW ................................. . ................. 91
TABLE 15 MATCHED PAIRS COMPARISONS .................................................................... 99
TABLE I6 CORRELATION MATRIX AND DESCRIPIIVE STATISTICS .......... 104
TABLE 17 FINAL PATH MODEL (STANDARDIZED) COEFFICIENTS 109

 

TABLE 13 POWER ESTIMATES BY FIT AND SAMPLE SIZE (MACCALLUM BROWNE, & SUGAWARA, I996) ....... 1 1 I
TABLE I9 MATCHED PAIRS TESTS OF DIFFERENCES OF MOTHER'S AND CHILDREN'S REPORTS OF GRADES....I 15

TABLE 20 OVERVIEW OF PATHWAYS PREDICITNG CHILD'S DESIRED JOBS BY ECOLOGICAL LEVEL ................ I 19

 

TABLE 21 CAREER ASPIRATTONS BY CHILD DEMOGRAPHIC CHARACTERISTICS 120
TABLE 22 PAIRWISE CORRELATION MATRIX OF DESIRED AND EXPECTED CAREER ASPIRATTONS OVER TIME

122

 

TABLE 23 OVERVIEW OF SURVEY RESPONDENTS (MOTHERS) RESIDENTIAL MOBILITY ................................. 123

List of Figures

FIGURE 1 INDIRECT AND DIRECT EFFECTS OF RACE ON ASPIRATTONS (PATH ANALYSIS OF SOLORZANO’S 1992

 

 

DATA) .......................................................................................... 7
FIGURE 2 BRONFENBRENNER’S ECOLOGICAL MODEL ......................................................................................... 23
FIGURE 3 PROPOSED ECOLOGICAL STRUCTURAL EQUATION MODEL .................................................................. 71
FIGURE 4 PREDICTED MODEL OF CHILDREN'S CAREER ASPIRATTONS ............................................................... 107
FIGURE 5 FINAL STRUCTURAL EQUATION MODEL ........................ 108
FIGURE 6 PERCENT OF CLIENTS CHANGING ADDRESSES FROM THE PREVIOUS MONTH (BY MONTH) .............. 123

Chapter 1 Introduction and Overview
Overview of the Present Study
The present research will use an ecological model (Bronfenbrenner, 1977) tO
examine the impact of individual, mother, and community level human capital on the
career aspirations of children whose mothers’ were receiving public assistance. These
factors will be examined for their potential influence on the prestige (Stevens &
Feathennan, 1981) of jobs that children aspire to achieve and the jobs that they expect to
achieve. The prestige of children’s career aspirations will be measured by the earning
potential and education levels associated with children’s preferred and expected job
choices. It is anticipated that these prestige levels will be influenced by the types of human
capital residing within the child, family and community. Human capital is “created by
changes in persons that bring about new skills and capabilities that make them able to act in
new ways” (Coleman, 1988: 8100). Human capital has been described as an important
predictor to achieving such career goals, including assets such as labor force participation
and educational attainment (Becker, 1964) that are associated with career progression,
earnings (Harris, 1993) and the quality of the learning environment for children
(Marjoribanks, 1991b). This research extends the definition of human capital to include
psychological resources, specifically self-competence, since self-perception relates to
achievement (Gecas, 1989) and may impact one’s ability to attain career goals. Therefore,
human capital assets of educational attainment, job attainment, and self-competence will be
studied at the individual, family, and community levels as appropriate. The present research
will examine whether these effects are direct or indirect, and whether children’s career

aspirations are influenced by age, gender, or race. Given the long-term economic

1

importance Of children’s career choices, this research aims to identify potential intervention

levels that will facilitate children’s’ transition out of poverty.

Outline of the Dissertation

The remainder of chapter one will discuss the importance and potential
contributions of this research to theory and practice. Chapter two will provide a literature
review with an overview of broad theoretical frameworks that served as the foundation for
this research. This includes an overview of the career development process within the
context of early and middle childhood. In addition, several theories that describe how
children filter influences fi'om their surrounding influences will be reviewed and linked to
career development processes. Additional literature will be reviewed to document existing
studies on general individual, family, and career characteristics that have been related to the
development of career aspirations.

Chapter three will provide a description of the hypothesized model predicting
career aspirations. Rationales for inclusion of specific variables and the links among the
variables will be provided. Some constructs in the proposed model represent new fi'ontiers
of research on career aspiration and will draw from the broad theories rather than specific
lines of research Since they are not yet developed.

Chapter four will describe the research method employed in this study. A
description of the random selection and recruitment procedures, along with the challenges
to data collection will be provided. The research sample will be described in terms of
major demographic variables including geographic mobility and will be analyzed to

statistically compare the research sample with the random sample on these demographic

2

variables. Measurement constructs will be operationalized and the structural equation
model will be presented.

Chapter five will present results of the data analysis. Findings will be presented for
the proposed model using the entire research sample and with subgroups to determine if
there are any effects for race or gender. The final path models (for the full group and
subgroups) will describe which variables and links were supported, modified, or excluded.
Overall goodness of fit measures will be provided for each path model.

Chapter six will provide a discussion of the key findings and their implications.
Support for expected findings will be highlighted for their contributions to this field, and
reasons for any unexpected findings will be explored. Limitations Of the study will be
discussed. In light of the research findings and limitations, implications for future research

and practice, including policy initiatives and action-oriented strategies will be considered.

Social Significance of the Present Study

 

The present research addresses childhood career choices that have important
ramifications for long-term economic success for the many children living in poverty and
may provide a partial explanation for the intergenerational transmission of poverty. Nearly
21% Of the children (roughly 14,000,000 children) in the United States were reported to
live in poverty (United States Census Bureau, 1996) and 9% lived in extreme poverty (Kids
Count, 1995). Furthermore:2i6% of children lived in single-headed households (Kids
Count, 1995) which have been predominantly headed by women (Lord, 1993) who also
suffer aggefipenaltyafqrhaving children that carmot be fully explained by time out of the

labor market, employment levels, or individual differences (Waldfogel, 1997). Therefore,

.cH-aramu—a. .........~.-__.— _.—

3

a substantial ntunber of children may be vulnerable to having lower career aspirations as a
function of their impoverished community of residence. This vulnerability presents a long-
term risk for economic success in adulthood for many children. The magnitude and
severity of these consequences demonstrate the need for focused attention on the

development of career aspirations of children living in poverty.

Aspirations impact later achievement

 

The careers the children aspire to achieve, even those aspirations expressed at an
early age, are important because they may predict actual career involvement as adults.
Longitudinal studies have found that young adult professional attainment was predicted by
earlier career aspirations. A longitudinal analyses of Swedish females found that the
motivation to pursue further education expressed at age 15 (in 1970) was strongly and
positively related to education and vocational choices at age 26 in choosing careers versus
home-making Q = 0.56, p<.001; Gustafson, Stattin, & Magnusson, 1992). Other
longitudinal assessments have linked the childhood preferences with the general types of
jobs held as adults. Trice & McClellan (1993) examined the types of careers preferred by
males and females from ages 6 through 17 (during 1922) and the types of careers they held
at age 30 (from follow-up surveys in 1936 and 1940). Children’s occupational preferences
and their actual careers as adults were coded into six themes‘including trades, scientific
occupations, artistic, helping professions, person-oriented business professions, or data-
oriented business professions. Over half of the children were in their desired career
category as adults by age 25 to 27 (See Table 1). Although Trice & McClellan (1993)

found a relationship between preferred careers and actual careers based on occupational

4

type, Levine & Zimmerman (1995) found a weak relationship between the sex-type of jobs
desired by 14 to 16 year olds (from 1968 and 1979 cohorts) and the sex-typing of actual
jobs attained at age 25 to 27 (from 1979 and 1990). This suggests that women’s actual
lifestyles reflected early choices to pursue homemaking or a career outside of the home.
However, once in a career path, males and females were not limited to earlier preferences
for careers associated with a particular gender, but they did remain in their general category

of occupational interest.

Table 1 Percent of children employed in their desired career (Trice & McClellan, 1993)

 

 

 

Career preference at age: Percent employed in preferred career at age 25-27 N
Males 6 to 9 54% 39
10 to 13 66% 83
14 to 17 65% 46
Females 6 to 9 56% 25
10 to 13 69% 39
14 to 17 71% 7

 

Career choices linked to intergenerational transmission ofmverty

Childhood career choices are important for their long-term impact on adult earning
power and this is an especially important consideration for children in poverty. Because
childhood career aspirations tend to replicate the socioeconomic class of the family
(Gottfi'edson, 1981; Jacobs, Karen, & McClelland, 1991), children living in poverty may be
more likely to aspire to lower-paying careers that may be Similar to their parents. After
observing male students beginning at age 15 and continuing until they were 26, Jacobs,

Karen, & McClelland, (1991 found that the students from lower socioeconomic classes
5

aspired to significantly lower-status jobs compared to upper socioeconomic class students
Lr= 0.17, p<.001) and the disparity in these educational aspirations between social classes
increased as students progressed through adulthood. When the present author recreated
Solorzano’s (1992) dataset1 and submitted it to a path analysis (See Figure 1), such class
differences were found to be stronger predictors of children’s career aspirations (p = 0.24,
95 % confidence interval = 0.22 5 p 5 0.22) than either race (p_= -0.04, 95% confidence
interval = -0.02 5 Q 5 -0.06) or gender (p= 0.00, 95% confidence interval = -0.02 5 Q 5
0.02). Based on these findings, children growing up in homes receiving public assistance
would be expected seek employment in lower-paying jobs. Such jobs may not provide
adequate financial support, much less provide upward mobility, and could leave them
underemployed and seeking public assistance themselves. Career decision-making is one
mechanism for the replication of social class, and it provides one explanation for the

intergenerational nature of poverty.

 

' Data were recreated based on the original author’s report of what percent of the sample (classified
by subgroups of race, gender, and socioeconomic status) aspired to low, middle, or professional jobs. Data
were coded using categories noted in figure 2.

6

 

I =Black
2=White

   
   
    

 

 

-0.04 (95% C1 = -0. 02 to -0. 06)

 

0.24 (95% CI = 0. 22 to 0. 26)

 

 

 

 

 

 

 

 

 

 

G (1 Career Aspirations
,f‘} e' , 0.00 (95% CI = -0. 02 to 0. 02) I=Iow
' em“ 2=middle
2=Male 3=professional
0.24 (95% CI=0. 22 to 0.26)
SES
1 =Iow _
2=low-middle N—1 3427
3=middle-high
4=high X2=10.96 (df=1) p=0.000

 

 

 

 

 

 

Figure 1 Indirect and Direct Effects of Race on Aspirations (Path Analysis of Solorzano’s
1992 data)

Importance of considering earning potential in career choices

While earnings may not be the only or most important aspect of a quality job, it is a
critical element Of a job that will enable children living in poverty to meet their basic needs
and have access to greater choices and opportunities in life as working adults. Because
children fiom economically impoverished communities or families may at risk for entering
careers associated with lower earnings, their career choices may determine whether or not
they have a minimum level of self-sufficiency versus remaining in poverty. This is unlike
children with higher socioeconomic backgrounds where the economic rewards associated
with their career choices may only differentiate between different levels of income that are
well-being poverty levels. Therefore, earnings provide a measure of whether or not a job
can meet the threshold of economic self-sufficiency that is not ofien associated with many

of the low-paying jobs held by adults receiving public assistance.

Underemployment is critical issue among public assistance families

 

It may be the socioeconomic status of jobs that may be most responsible for a lack
Of economic self-sufficiency, rather than unemployment. The majority Of welfare recipients
have been employed (Kossek, Huber-Yoder, Castellino, & Lerner, 1997) but have
remained in poverty because job earnings have not been high enough to support the
household (Edin & Leirr, 1996). A survey of welfare recipients with children in early Head
Start programs, in which clients must meet a low-income eligibility guideline, found that
two-thirds of the recipients were receiving wages of less than six dollars per hour (Reischl,
Schimnan, & Huber, 1998). However, current estimates suggest that a wage of $10.39 an

hour is needed for a family of four with one earner to achieve economic self-sufficiency

8

and provide for basic living expenses (Michigan League for Human Services, 1998).

These findings indicate that just being employed does not alone guarantee economic self-
sufliciency and that attention must be given to the quality or type of careers that children
aspire to at an early age. The public policy issue of paying a_r_ry workers less than living
wages should not be dismissed, however, it is clear that children living in poverty may need

additional help overcoming baniers to choosing higher paying jobs.

Impact Of unemployment on families

 

Unemployment may have a negative impact on children and families that may
ultimately impact career aspirations. In a study of children affected by the widespread rural
farm crisis, Van Hook (1990) found that the economic distress increased family tensions
and decreased communications within the family which may be important during the career
exploration process. Furthermore, the stress had a negative impact on school performance
that could limit further career and educational plans. It also led many adolescents to stay
away from home to avoid the negative situation. These economic stresses may have
limited students’ ability to utilize resources, such as parents and education, to help them in
their career planning.

Unemployment may also negatively impact the psychological well-being of
individuals who have suffered a role loss as a provider and may have feelings Of
inadequacy (Aubry, Tefli, & Kingsbury, 1990). This may result in lower self-esteem
(Keefe, 1984) or it might result in more serious forms of depression, substance abuse, or
violent or neglectful behavior toward family members (Shelton, 1995; Steinberg, Catalano,

& Dooley, 1981). Such negative occurrences may translate into more stress beyond what

9

was already experienced due to financial strain. However, it is important to note that
individuals have difierent reactions to unemployment. When unemployed, women were
found to engage in non-work activities such as house, car, or garden improvements which
was positively related to self-esteem or spending time with children but this was associated

with increased levels of depression (Shamir, 1986).

Limitations in existing literature

In addition to addressing contemporary pressing social issues, the present research
also seeks to address limitations existing in the scholarly literature. This research addresses
the limitations of existing research, which includes (1) an individual-level bias with limited
attention to contextual influences on career aspirations in selection of predictor variables,
and (2) an exclusion of children living in poverty or receiving public assistance benefits in
research samples. An overview of these limitations is presented.

Individual level analyses have dominated research on career develgrment

Psychological research has been criticized for failing to examine variables beyond
the individual level of analysis, or for measuring community-level variables using
individual-level data (Shinn, 1990). Like much psychological research that has not gone
beyond the individual level of analysis, research on predictors of vocational development
has focused heavily on individual difference factors. Personality, identity, ability, and
demographic variables as a group have been studied quite often in relation to career
aspirations and motivations. Much less attention has been focused on variables outside of

the individual level.

10

Contextual factors under-studied in research on career development

Although variations in children’s social contexts can lead to different goal
orientations in life (Klaczynski & Reese, 1991), these factors have been studied less than
individual factors in career development for their role in shaping vocational outcomes. In
the present literature reviewed, a limited number Of studies were found that assessed
contextual factors, such as the family and the community, relative to career development.
These few studies assessed such family characteristics as educational background, parental
employment, parental expectations in career aspirations and general career development
(e.g. Jacobs, Karen, & McClelland, 1991; Levine & Zimmerman, 1995; Marjoribanks,
1991a; 1991b; 1993; 1995; 1996; Man, Dominick, & Ellsworth, 1995; Maxwell, &
Maxwell, 1994; McCullough, Ashbridge, & Pegg, 1994; O’Brien & Fassinger, 1993;
Penick & Jepsen, 1992). Although family educational and employment characteristics
were measured for their impact on career aspirations, the impact of the community
economy was largely ignored despite the role of the economy in shaping the local
educational and employment opportunities.

Poverty overlooked in career planning research

 

A limited number of studies have considered contextual influences in the
development Of career aspirations, and even fewer studies have examined community level
measures Of socioeconomic status in relation to children’s career aspirations. In these
studies researchers considered the vocational plans of children from a nrral town (Penick &
Jepsen, 1992), an urban area (Empson-Warner & Krahn, 1992), and from national samples
(Mau, Dominick, & Ellsworth, 1995; Solorzano, 1992). These studies suggested that

socioeconomic status influenced vocational aspirations. However, these studies did not

11

specifically focus on children at the lowest end of the socioeconomic status continuum,
despite the importance discussed earlier. Socioeconomic background has been found to be
a key predictor of future career aspirations among non-poverty populations (Solorzano,
1992). It may be reasonable to expect the effects of class to be magnified for children at
the lowest end of this spectrum given the potential lack of access to human capital within
the family or neighborhood. Furthermore, the assumptions of how individual, family, and
community human capital predict career aspirations in middle class families may not be
true for families in poverty. Because little is known about the specific development of
career aspirations among children living in poverty, it is important to examine this sample
more closely to understand the unique challenges faced by this growing population.

Developmental process not reflected in research designs

 

Much of the research on the career aspirations of children has focused on single
predictorresearch variables. This ignores the complexity of the developmental process in
which multiple influence variables are present and may interact with one another. With
the notable exception of Rojewski & Yang’s (1997) longitudinal study of career aspirations
in a non-poverty sample, developmental studies of multiple level influences on career
aspirations are scant. Therefore, multivariate research designs are needed in the study Of

influences on children’s career aspirations.

Purpose of this study

 

The present research seeks to advance knowledge about the career development of
children receiving public assistance benefits, and to define some of the potential barriers

that prevent these children fi'om aspiring to high paying jobs. Childhood career and

12

educational choices are central to economic empowerment as adults. Therefore, the present
research focuses on predictors of the status of jobs that children aspire to achieve and the
jobs that they expect to achieve. Unforttmately, children living in poverty have been
extremely underrepresented in the career aspiration development literature, despite the
critical importance of career planning for this economically vulnerable population. This
research focuses on the understudied population of children in poverty utilizing a multilevel
approach that goes beyond and assessment of individual differences. The present research
will examine the impact of individual, mother, and community level human capital on the
career aspirations of children whose mothers’ were receiving public assistance using an
ecological model (Bronfenbrenner, 1977). In considering these potential multiple
influences on career aspirations, the present research utilizes a quasi-longitudinal model
that includes baseline data along with two measures over time to enhance scholarship in the

study of this under researched population.

Contributions of this research

 

Several contributions to theory and practice are expected as a result of the present
study. The present research will seek to correct the individual level bias present in career
aspiration research by including variables from multiple levels. Family and community
level variables will be included with the analysis of individual level variables to examine
the context of children’s development, rather than just the children alone. In addition,
community level variables will be examined using archival data sources specific to the

neighborhoods in which the survey respondents live (Shinn, 1990). The use of this archival

13

data provides indicators of structural conditions in the community that augments perceptual
or self-report data.

The present research will also examine the influence of the community economy on
youth occupations, rather than visa versa. Research has Often been concerned with how to
use human capital to meet the demands of the workplace (Hagemo, 1997). Conversely, the
present research seeks to understand how the workplace may contribute to the growth or
stagnation of the community human capital.

To address the lack of class diversity among research samples in the existing career
aspiration literature, the present research will focus on a sample of children from low-
income households. Although the full model cannot be examined over time due to
tremendous difficulties obtaining a large sample size with this understudied population,
some post-hoe analyses will examine changes in career aspirations over time to add a more
developmental perspective. These unique elements of the present research seek to address
some major gaps in the research knowledge base and methodology regarding occupational
aspirations. It is expected that this research will integrate and expand existing theories and
will contribute to the development Of action-oriented strategies to improve career outcomes
for children living in poverty. From these advances in theory, it is expected that results will
promote strategies to reduce poverty by showing the importance of increasing children’s

access to human and social capital during their career planning process.

14

Chapter 2 Literature Review

Importance of Career Development in Early and Middle Adolescence

Middle childhood and early adolescence is a time when important cognitive and
social developments occur and can have an influence on career development. Career
decisions in middle childhood and early adolescence occur during a time of identity
formation, values clarification, individual growth, exploration, and increasing self-
awareness and developmental changes in physiology, cognition, and social skills and it is a
time when children begin to learn skills that will prepare them for eventual employment in
their own culture (Erikson, 1975; Mitchell, 1986). The questions of "Who am I?" and
"What is my role?" are central not only to )adolescent development, but to the career
exploration process as well. These developmental processes are influenced by children’s
cognitive development as well as their social development and learning from the word
around themselves.

oflnhelder & Piaget (1958) indicate that these age periods are marked by important
cognitive developments. By the ages of 8 to 10 children are capable of concrete
Operational thought so they can use logic to reason and have a sense of right and wrong not
complicated by the complexities of moral ambiguities of adolescence. After age ten
children have more formal operational thought where possibility rather than reality is
emphasized. By middle childhood and adolescence children have developed cognitively to
the point where they can understand and be aware of the differential prestige for various
occupations (Miller, 1988). However, this awareness may be constrained by a limited

exposure to career options due to ones’ socioeconomic circumstances (Gottfredson, 1981).

15

Therefore, it is important to understand how multiple influences from the community,
family, and within the child, contribute to these important career decisions being made
during childhood and adolescence.

By middle childhood, children become more attuned to learning by imitating Others
around them and they become more responsive to external reinforcements (Bandura, 1977).

During this time children find that they have skills in different areas which may guide their
career interests and parents’ influence is still important. At this age children receive more
parental reinforcement of these skills, receive more advice or suggestions of how to apply
these skills to a particular career than at older ages, and are more likely to be influenced by
these career suggestions at this age than when they are older (Trice, McClellan, & Hughes,
1992). Although parents and teachers may reinforce children's strengths by encouraging
them in certain directions, if children have limited experiences to develop self-competence
or are slow to develop, they may be prematurely diverted to a narrower range of career
possibilities and preparation Since self-concepts are not yet finalized during middle
childhood (Rutter, 1992). Together these developmental tasks related to cognitive and
social growth, prepare the way to allow young people to go forward in establishing an
individual identity and a societal role within a larger commtmity. It is also important to
understand how these individual developmental progressions occur within a family and
community context of the ecological framework.

Theories of Person in Context Histog
In this study, career development will be analyzed within the ecological paradigrn
(e.g., Barker, 1968; Bronfenbrenner, 1977; Kelly, 1968; Moos, 1973). This paradigm

emphasizes the importance of both individual differences and environmental influences in

16

predicting outcomes and provides the overall framework for the measurement model
employed in the present research. Within this theoretical tradition, individual career
development outcomes can be seen as a product of both individual and environmental
factors which contradicts the historically individual bias present in the behavioral sciences
in general (Cronbach, 1957; Lewin, 193 5), and more specifically, much of the literature on
career development. To correct for the individual bias, ecological scientists had to develop
theories and methods for understanding how environments influenced individuals. An
overview of these multiple perspectives is provided to demonstrate the multifaceted
approach that has been used to examine the environmental context of individual’s
development.

Early in the history of the ecological paradigm, initial conceptions of the
environment focused on physical aspects. Kantor (1924) defined the environment in terms
of is physical qualities and theorized that the physical environment provided a stimulus
which produced a response, thereby creating the psychological climate. Koffka (1935) also
focused on the physical aspects of the environment, saying that the individual behavior was
a function of the interaction between the individual organism and the physical environment.

In a similar fashion, Lewin (1935) took an interactional approach, saying that behavior was
a function of the interaction between the person and the environment rather than either one
independently. However, this theory was not as focused on the physical definition Of the
environment as previous theorists were.

AS the theory grew, the definition of the environment grew more complex and
began to consider how individual differences could influence the impact of the

environment on individuals. Murray (193 8) added to previous views of the environment,

17

noting that both subjective and objective environmental presses, along with individual
personality needs, interacted to produce behavior. Stern (1964) later expanded on Lewin's
(1935) theory of B=f(P,E) and Murray's (1938) theory of environmental presses by
stressing that the congruence of personal needs and environmental presses must interact to
maximize outcomes. Cronbach (195 7) pioneered the aptitude-treatment-interaction (ATI)
method to understand how successful treatment outcomes could be maximized by
understanding the interaction between individual abilities and various treatments. These
theorists expanded the definition of the environment to go beyond physical attributes, to
include subjective definitions that took into account how individuals perceived their
environments and how individuals needed different things from the environment to
produce the best outcomes.

As the ecological theories became more complex, additional attention was given to
applying the theories in various settings. Kelly (1968) applied biological ecology
principles to the ecological psychology paradigm. Kelly used this paradigm to
understanding social change and how to plan community interventions within settings.
Barker used the concepts of interdependence, cycling of resources, adaptation, and
succession to describe the struggle undertaken by communities and individuals having to
adapt to changes in the environment. Barker (1968) more fully explored the concept of the
setting and created techniques for assessing the physical concepts of the natural settings,
with spatial and temporal dimensions, that influenced behaviors. Barker created the
“behavior setting” to define a specific place and time that also was defined by the social
expectations for behavior in that place and time. . So rather than just focusing on a physical

description of the environment, or the individual perception of the environment, Barker

18

included social aspects of the environment that superceded an individual’s isolated
perception of the setting.

Continuing with the interest in applying theory, the ecological paradigm was used
to try to create better classroom situations. Pervin (1968) promoted the use of the
Transactional Assessment of Person and Environment (TAPE) method to study the
interaction of these variables to determine which patterns produced better outcomes for
student achievements. Similarly, Hunt (1974) focused on finding the best fit between
students’ cognitive or conceptual level and various classroom structures to produce the best
learning outcomes for students. These early measures assessed individual and
environmental characteristics that could be combined for positive school related outcomes
in the immediate time frame.

After a time, ecological assessments became more focused on multiple levels of
analysis. Bronfenbrenner (197 7) promoted the analysis of multiple levels of nested
systems and relationships that embedded individuals. This theory emphasized social
relationships as a primary determinant of the environment, and that individuals were
influenced by people in their most immediate surroundings, who would in turn, filter
influences of external social structures. Forces much beyond the immediate context were
considered important in this theory. Cultural and religious ideals, mores, economic
systems, legislation, and other extemal factors were purported to influence individuals.
These influences were seen as primarily indirect, filtering through other social structures
before reaching the individual. In this theory, social structures most proximal to the
individual have the most influence. Moos (1974) also saw the importance of the social

aspect of the environment and incorporated that perspective into the climate scales

19

designed to assess the social-psychological sense of environment. Climate scales focused
on systemic, relational, and personal development attributes of the environment.
Bronfenbrenner and Moos’ frameworks brought additional focus on the social dimension
of the environment and introduced more sophisticated approaches to measurement of this
social environment.

Reciprocal forces have been included in more recent frameworks. The theory of
developmental contextualism (Lerner & Lerner, 198 6) has incorporated the notion of
dynamic interactionism and has been particularly applied to studies of children and youth.
This theory suggests that children are influenced by multiple contexts (e.g. time, place,
family), and it also adds the theory of bi-directionality, which is also a component of
system dynamic theories (Levine & Fitzgerald, 1992).. This states that children can
influence their contexts, which in turn can influence the children, creating this dynamic
interaction between the child and the family system. This reciprocity has been recognized
in the stage-environment-fit theory (Eccles, Midgley, Wigfield, Buchanan, Reuman,
Flanagan, & Mac Iver, 1993). Findings have supported this theory that states personal
needs and preferences change according to developmental stages, and that individual
outcomes can be influenced by the environments’ ability to respond to these maturational
needs. These more recent theories advanced the importance of the social dimensions and
social structures when defining the context of human development, particularly for

children.

20

An Ecological Framework

The development of the ecological framework has enabled researchers to
understand children’s developmental progression within a context of multiple influences.
The development of career aspirations is one developmental task that can be examined
within this context. Based on this multi-faceted framework, one could theorize that aspects
of the physical, social, and psychological environments surrounding children may have an
influence on the children’s career choices. These influences may be direct or indirectly
filtered through others in the immediate proximity of the child. Career needs of children
may differ based on their own characteristics, and the fit between the child’s personal needs
and resources in the environment may determine the quality of the career development
progression. As children grow older, their needs and their relationship to the environment
may change. Therefore, parental career advice may have a different influence on the
developing child’s career aspirations at different ages and maturation levels. Given the
dynamic relationship between children and their family environments, the child’s reaction
to parental career assistance may determine how the parent approaches the child during
future discussion of careers. These ecological theories highlight the potential importance
of contextual, as well as individual, factors in the development of career aspirations as a
main task of childhood development. To provide a specific fiamework for the review of
existing literature on career aspirations, Bronfenbrenner’s (1 977)}591315993 model

will be used.

21

Nested Systems: A Specific Ecological Approach

Bronfenbrenner’s (1977) ecological framework employed a nested systems
approach. This framework uses a multi-level system to classify the social structures that
impinge on the development of individuals. The four systems include the micro- meso-
exo- and macrosystems. The individual is directly imbedded within the microsystem,
which is nested in the exosystem, which is in turn nested in the macrosystem. The
interactions between the microsystems constitute the exosystem. In this framework, the
developing individual is imbedded within these concentric circles representing the multiple
levels.

Figure 2 shows a sample of this nested system for a developing child. The
microsystem includes the interrelationships between the individual and the immediate
environment and directly influences the child due to its close social proxinrity to the child.

For children, the family is considered a primary microsystem, but may also include school,
sports, or other clubs that directly involve the child. The role of these different
nricrosystems may change over the course of a child’s development. The exosystem
identifies influences beyond the individuals' direct environment, including formal and
informal social structures of the larger community in which an interaction between
microsystems could impact the child. Examples of children's-exosystems include school
boards, parent employers, local government, and the local economy. These forces may
directly or indirectly impact children. A youth curfew imposed by the city council or
school absence policies implemented by the school board would have a direct impact on
the child. An employer requiring overtime work might indirectly affect the child by

making it difficult for the parent to attend soccer games. An unhealthy community

22

economy may limit the economic opportunities of youth. On a much larger level, the
macrosystem is characterized by even larger social forces that often affect individuals
indirectly. The macrosystem includes entities such as the national government, cultural or
religious norms, ”CERES?! media. The national economy, welfare reform policies and
public opinion about public assistance clients are examples of macrosystems that could

indirectly influence children living in poverty.

 

Welfare Policies

—-.- er-

 

V Parent’s Employer

Fggtntly , V.) H PM
Child Individual“ 3 c ,
[IQYITt'KL )q, ’ .

C .9 ‘ i I - ’- _ .. 1.... _.
I” r '( W" TE"; "1. if .4". . I
r“ School Board \ . Exosysterrr' C), 5“,“,wa 8’

COT
' ‘ P ‘ . Mam-”St“ ( Fa.......~.~/(.w I

 

 

 

 

 

 

 

 

 

 

ECO‘IEEIEY
Figure 2 Bronfenbrenner’s Ecological Model

Reviewin Career As iration Literature from an Ecolo ical P ctive

 

Using nested system approach, career aspiration literature will be reviewed to
reflect selected individual, family, and community influences on children’s career
aspirations. The first three layers of the nested system reviewed above will be used to frame M A,
the literature review on children’s career aspirations. The firstly/er consists of the 613.; WA
In this first layer, variables related to the child’s individual characteristics will be reviewed

J
y éc‘$$l\\

as the first main category of aspiration predictors. The family is classified as theiétionil-
layer of the model. Characteristics unique to the family will be reviewed as the second
main category of predictors of career aspirations. Characteristics of thel comfngtylare the

exosystem variables to be reviewed as the third set of predictors in the review of the career

23

aspiration literature. Bronfenbrenner’s nested system theory provides a classification
scheme for the levels of variables that are important for assessing career aspirations from
an ecological perspective. This classification system will provide the building blocks for
the development of a measurement model to test the applicability of the ecological
framework to childhood career aspirations.

As stated earlier, most studies pertaining to the development of childhood career
aspirations reflect the bias toward individual attributes as predictor of career aspirations and
have not employed multilevel designs to incorporate the ecological model. There are a
limited number of studies examining family level variables, and even fewer reviewing
community level variables. By combining the existing studies that use single level variables
as predictors of career aspirations, the present model can compare and contrast the strength
of individual attribution theories and social allocation theories of career aspirations.
Through the testing and refitting of the model, the final model will reflect the appropriate
direct and indirect effects of these various theories in explaining career aspirations.
Individual ambitions have been used to explain the relationship between child background
and aspirations, but this relationship may also be explained by differential socialization of
children based on their background. Although this study does not explicitly measure
socialization processes, it could be one explanation for relationships found between study
variables. Children with this differential socialization may perceive that they have an
easier or harder time achieving certain types of careers because of the “gatekeeping”
functions or “social allocation” that occurs because of their background (Jacobs, Karen, &

McClelland, 1991). The expanded model to be tested in the present research will assist in

24

developing an ecological model of career aspirations allows for the simultaneous
comparison of individual and structural models used to explain career aspirations.

This section provides a review of the psychological literature on the development of
career or occupational aspirations using the ecological fiamework, and more specifically,
Bronfenbrenner’s nested systems approach. To assess the need for a multilevel approach to
this field of study, literature from the past decade was reviewed documenting research on
individual, family, or community level predictors of career aspirations for children and
adolescents up to the age of high school. The primary outcome variable in this literature
review was the quality of employment desired by the youth. Quality referred to the
economic or earning potential of the career or vocation that youth aspired to achieve. The
quality of career aspirations have ofien been determined by the socioeconomic status (SES)
of the job type aspired to by children, ofien measured by a prestige score or by the
educational level required for job. In other cases, the quality of the job was inferred from
the type of job, such as artistic versus scientific, or careers outside of the home versus
careers inside the home.

The broad categories of predictors identified in the recent literature using the
individual, rrricrosystem, and exosystem levels in Bronfenbrenner’s (1977) ecological
theory include child, family and community variables. Within each of those domains,
variables were classified within subgroups according to themes. Subgroup themes within
the child variables included child psychological well-being, child academic ability; and
child demographics. Family variables included parent employment, parent education, and
parent self-concept. Community factors included variables relating to economic
opportunities within the community.

25

Methods for summarizing literature

To provide uniformity among studies reviewed in this section, effect sizes will be
converted into a uniform metric of correlations whenever, rather than reporting original
eflect sizes of various types of statistics. Statistics reported as “non-significant” have
estimated effect sizes of zero if it was not possible to determine the effect size. Because
confidence intervals of effect sizes are often not reported or able to be computed, effect
sizes will be classified based on categorizations from Lipsey & Wilson’s (1993) review of
expected effect sizes in psychological research. From this review documenting the range
of expected effect sizes correlations will be designed small, moderate, or large which
corresponds with the lower, middle, and upper thirds of correlation sizes expected in
psychological research. Therefore, correlations from O to 0.10 will be considered small
effects, correlations from 0.10 to 0.23 will be considered moderate effects, and correlations
from 0.23 to 0.35 or larger will be considered large effects.
Influence of Child mfimDifferences on Career Aspirations

"T'" *-— “\J

Individual differences are important aspects of development. During this time of
development and maturation in early and mid adolescence when career aspirations are
developing, children experience changes in cognition, self-perception, and awareness of the
world around them (Erikson, 1975; Mitchell, 1986). This cognitive development has been
linked to positive understanding and involvement in career planning (Billups & Peterson,
1994). However, there are individual differences among children in their background,
maturation, abilities and their perception of their abilities (Harter, 1985). Such abilities and

resources are human capital assets believed to have an important role in shaping firture

26

successes (Coleman, 1988; Vroom, 1964). Therefore, the role of individual differences in
maturation, demographics, academic achievement, and self-perception and beliefs about
their abilities will be examined to estimate the size of their effect on career aspirations.
Academic Achievement

Academic achievement has had a strong effect on career aspirations (See Table 2).
Among 8th grade females, higher grades in math, science, reading and overall grade point
average were strongly linked to aspiring to a career outside of the home rather than home-
making (Mau, Domnick & Ellsworth, 1995). Such plans for an outside career may be more
certain to provide for individual economic self-sufficiency since home-making as a career
is likely to be dependent on another person’s income. Erickson (1994) found that higher
scores on math and science achievement tests were also strongly linked to preferring
careers with higher prestige, which is a combination of earning potential and education
required for the job. Similarly, general academic performance (Empson-Warner & Krahn,
1992) and grade point average (O’Brien & Fassinger, 1993) among high school seniors and
18-year-old students were strongly related to the SES and prestige of desired careers
respectively. Gifted high school students desired and expected to achieve higher prestige
careers than students with failing grades, and this effect was even stronger for expected
careers than desired careers (Manaster, Chan & Safady, 1992) suggesting that self-efficacy
beliefs about actually achieving one’s desired career may be" influenced by academic
abilities. Although these studies were limited in their focus on older students (8th to 12th
grade) and did not sample students from lower SES conditions, the studies did reveal that
students experiencing success in the school setting had preferences for higher status level

careers and potentially stronger self-perception beliefs about achieving career goals.

27

 

 

 

 

 

 

 

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29

Self-Efficacy and Self-Esteem

Child, adolescent, and young adult self-concept has been viewed as integral to the
development of an occupational identity (Erikson, 1963; Marcia, 1980; Super, 1957), and
has been linked to successfiil career planning (Chiu, 1990; Kawasaki, 1994), career
exploration (Wallace-Broscious, Serafica, & Osipow, 1994), and anticipated success in
one’s chosen career (O’Brien, 1996; Singer, 1990; Singer, Stacey, & Lange, 1993). More
specifically, the present review found that self-esteem generally had a moderate to large
impact on career aspirations (See Table 3). Among 8th grade females, self—esteem had a
large impact on the decision to select a career outside of the home rather than homemaking,
(Mau, Dominick, & Ellsworth, 1995). Self-esteem was positively correlated with the
prestige (earning potential and education required) of the desired careers of 8th 10th, and
12'h grade students and this effect was moderate (Erickson, 1994). In a similar study,
(McCullough, Ashbridge, & Pegg, 1994) self—esteem was non-significantly related to the
prestige of desired careers among 9th to 12th student leaders. The student leaders had higher
career aspirations than their non—leader peer counterparts but did not differ on self-esteem.
This non-significant finding may have been due to a small sample size (fl=203). It may
have also been due to a potential restriction of range on self-esteem levels among student
leaders. Although studies focused on older students (8th to 12th grades) and did not study
children in economic distress, they did find that for females self-esteem was associated
with selecting higher status aspirations since they chose careers over homemaking. For
both males and females, self-esteem was also related to choosing higher status careers in

general.

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31

Age and maturation

Age and maturation may impact career plans since cognitive development, self-
awareness, and growing awareness of careers are likely to increase with age. Although
career aspirations have been found to be reliable at all ages and stable over time, they have
also been found to become increasingly specialized with age. In assessing the reliability of
reported career aspirations among kindergarten, 2nd, 4‘“, and 6th grade students, Odom,
Woods, & McClellan, (1995) found that there was a strong correlation between first and
second career choices at all ages Q = .46, .37, .50, .61 , respectively) and that this reliability
generally increased with age. Not only were the career aspirations of these young children
reliable, they were predictive of future aspirations. In Trice & Knapp’s (1991) study,
approximately one hundred 11-year old students from a rural school and one hundred 11-
year olds from an urban school were asked to report their career preferences at two
different times. Eight-months after the initial interview, 45% of the girls and 45% of the
boys had the same career preferences as they did in the first interview. A different study
(Trice, 1990) found that 87% of 8-year-olds and 94% of 11-year-olds career preferences
were similar over one years’ time. Although career preferences remained similar over
time, they also became increasingly specific with age. Phipps, (1995) found that the
majority of even 8 to 11 year olds were able to articulate their reasons for choosing their
preferred occupation based on a growing awareness of their abilities and interests (3 8%),
desire to help others (15%), job earnings (14%), to follow a role model (10%), or for other
a variety of specified reasons (8%). Although career aspirations appear to be reliable and
consistent at even young ages, maturation adds to the clarity and specificity of

developmental tasks associated with selecting careers.

32

The prestige of career aspirations may also be consistent over time, but this
relationship is not clear, perhaps due to measurement issues (See Table 4). Erickson
(1994) found a small negative effective of grade level on the prestige level of career
aspirations among multi-ethnic 8th to 12th grade students. However, in a more
homogeneous sample Leung, Conoley & Scheel (1994) found that the prestige of desired
careers increase over time, but this was based on retrospective reports of 11th grade
students. In a third study, Marjoribanks (1991a) found that the combined effects of age,
gender, social status, and ethnicity had a very large positive impact on the prestige of
careers desired by 16 year old students, but it is not clear how much of this variance is due
to age alone. Studies empirically evaluating the relationship between age and career
aspirations focused on older students (8th to 12th grade) and did not sample students in
economically disadvantaged communities, however these limited findings suggest that age
may have an impact on the prestige of career aspirations, although other sources of life
experience such as race, class, and gender may moderate this relationship and should also
be considered for their impact on career aspirations.

Slander

Because of differences in childhood socialization experiences, gender has been
though to play an important role in career choices (Eccles & Hoffman, 1984). Through this
socialization process, gender appears to have a direct effect on various aspects of career
aspirations. A review of research from the 1940’s through 1960’s (Marini, 1978) reported
patterns of lower career aspirations among women and that gender affected occupational
attainments indirectly through educational attainments, occupational aspirations, self-
perception, attitudes and expectations of others. However, with changing external

33

 

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34

conditions, social attitudes toward women in the workplace, and the prevalence of women
in the workplace, these gender effects may be mitigated in the present time in history. A
review of current research on gender and career aspirations shows some evidence of a
reversed trend, although the results are still mixed.

An overview of gender and educational aspirations in Table 5 shows that women
consistently desired careers with higher educational levels than males desired. These
correlations were moderate to strong across all the age groups. Females as young as 4
years old desired careers with more education than males and this gender effect persisted
through at least through 8'h grade. For females, educational investments may be an
important indicator of a quality career path.

Although educational levels associated with careers were significantly higher for
females than males, the actual prestige or status of desired careers showed a curvilinear
gender effect. Prestige measured jobs in terms of their earning potential as well as the
education required for the job on a scale ranging to 100, and job status provided a similar
measure based on limited categories of low to high. Table 6 shows that males desired
higher prestige careers than females, although this correlation was either large Q = .27 to
.39 or very small Q = .01 to .05). Conversely, females were likely to aspire to higher status
careers with the correlation being small Q = .01 to .08) to moderate Q =.20). While the
small sample of studies does not permit moderator analyses,“ there do not appear to be any
patterns of moderator effects due to age differences or ethnic differences although further
studies of these interactions is warranted. The explanation of these mixed findings may be
attributed to the measurement of the status of career aspirations and gender differences in

the types of careers desired. These studies suggest that education level and type of career

35

may be more important than earnings in distinguishing the careers desired by each gender,
although there are no studies of children from economically disadvantaged communities in
these comparisons.

Gender has been more predictive of the education level, occupational theme, or
purpose of a given career than its earning power. The review (see Table 5) of gender and
education level of desired jobs showed a clear relationship with females aspiring to jobs
with higher educational requirements. There are also clear gender effects for the types of
jobs desired based on sex stereotypes. As young as age four, boys preferred jobs traditional
males jobs (I = .44) and girls preferred traditional female jobs (r = .66) according to Trice
& Rush (1995). This trend was also found in Kindergarten to 8‘“ grade students with males
being much more likely than females to prefer careers considered as “male” jobs (r= .53;
Etaugh & Liss, 1992). Similarly, among multi-ethnic Kindergarten through 6th grade
students there was a strong likelihood that girls were more likely than boys to aspire to the
jobs of their mothers (r = .26) and a small likelihood that boys would be more likely than
girls to aspire to have the job of their father (r = .06, Trice, Hughes, Odom, Woods, &
McClellan, 1995). Furthermore, boys were much more likely than girls to aspire to math or
science careers (r = 0.15; Gassin, Kelly & F eldhusen, 1993) or careers that were considered
adventurous Q =.41), investigative/scientific Q = .25), or realistic/trades Q = .72) while
females were more likely to choose social/helping Q = .54) or conventional/data—oriented
business careers Q = .48; Lapan & Jingelski, 1992). Gender effects were also found for the
purpose of a desired career. Gender has also been important in choosing jobs based on
values or job purpose. When citing reasons for selecting their desired careers, economic

issues were more important to slightly more males (15%) than females (13%) and altruism

36

was much more important to females (24%) than males (6%) according to Phipps’ (1995)
study of eight to eleven year old students. Therefore, females and males have clear
preferences for different types of j obs, but earning power may not directly correspond with
these types.

Although gender has predicted career choices based on occupational theme, sex
stereotype, or educational level, prestige scores do not necessarily align with these career
types. Using recent prestige codes (Stevens & Cho, 1985) it is possible to see that there is a
large variation in the prestige of careers that males may aspire. For instance, these jobs
could range from scientific careers such as chemical engineering (prestige = 87.14 ) to
specialized trades such as air conditioning repair (prestige = 26.38). Furthermore, there is a
wide range of variation even within the same type of job categories desired by females.
Social careers desired by females could range from physician (prestige = 88.37) to child
care (prestige = 23.06). Conventional data-oriented careers desired by females could range
fi'om computer systems analysts (prestige = 74.10) to bookkeeper (prestige = 29.65).
Therefore it may be reasonable to expect gender to have mixed results when examining its
influence on career choices by prestige or status. Furthermore, the nature of this
relationship between gender and earning power of occupational choices may not be clear
for all children since these studies did not include children from economically
disadvantaged communities and did not include children under the age of 11.

In addition to direct gender socialization effects, there may be other processes
indirectly related to the gender differences in career aspirations. Role modeling may be

more influential for females, compared to males.

37

Economic distress also appears to affect males and females differently. In a
longitudinal study of Canadian 12th graders socioeconomic status was related to
occupational aspirations one year following graduation; however, this relationship was
positive for males and negative for females (Empson-Wamer, & Krahn, 1992). In single
female-headed households daughters were more at risk than sons for aspiring to lower
prestige careers (Shapiro & Crowley, 1982; Waite & Berryman, 1985). However, in other
studies, males career choices appear to be more vulnerable to economic distress. Among
rural 9th to 11th grade at-risk-students, males aspired to significantly lower status
occupations when compared with females (Rojewski, 1995). Economic distress effects
both males and females, although the influences may be different for each gender.

The influence of gender on career choices may not be lasting. Levine &
Zimmerman (1995) assessed the career preferences of two cohorts of females aged 14 to 16
in 1968 and 1979. Their career choices were rated as female-dominated, male-dominated,
or integrated. The actual occupational achievements of these women were assessed in
follow-up studies when the women were between the ages of 25 and 36. The sex-type of
the desired during high school was not strongly related Q = .08) to the sex-type of the
actual career during mid 20's or mid 30's. The authors concluded that the opportunity
structure of the labor market, rather than childhood socialization, shaped women's career

choices. The role of socialization may be countered by post-high school experiences.

38

 

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41

RE

The present research fount inconsistent support for race as a direct influence on
career aspirations (see Table 7), but a re-analysis of existing data suggests that race may
primarily have an indirect effect on career aspirations. Some small to large direct effects
were found between race and types of careers. Marjoribanks (1996) found that Greek high
school students had higher job expectations than either Anglo-Austrialian or Southern
Italian although this was primarily attributed to differences in the regional economic
conditions. In a study of low-income children Phipps (1995) found that African-American
children aspired to occupations with higher educational requirements compared to the
White or Hispanic children. Asian-American and Black-American girls were more likely
than White-American and Hispanic-American girls to choose science/engineering careers
over homemaking (Mau, Dominick, Ellsworth, 1995). These findings may reflect different
cultural priorities for education and career achievement.

However, race was not found to be a significant predictor of the actual prestige of
desired jobs. Among various studies of 11 to 17 year old students of various ethnic
backgrounds, no significant effects were found (e.g., Bronzafi, 1991 , Hauser & Anderson,
1991, Jacobs, Karen, & McClelland, 1991, Kelly & Cobb, 1991, Solorzano, 1992). Based
on a reanalysis of existing data, there is evidence to suggest that the influence of race on
career aspirations may be masked by effects of socioeconomic status (SES).

In a study of 8th graders (Solorzano, 1992), white students appeared to have higher
career aspirations than black students when looking at individual variables alone. However,
when the present author of this dissertation submitted the recreated dataset to a path

analysis and the effects of SES were partialled out, black students had higher career

42

aspirations than the white students did (p = -0.04, conf 95% = -0.02 5 Q 5 -0.06) as noted
previously in Figure 1. Without considering socioeconomic status, black students tended to
have higher aspirations than white students did. However, black students had lower
socioeconomic statuses than white students did (p = 0.24, conf 95% = 0.22 5 Q 5 0.26) and
lower SES was associated with lower career aspirations (p = 0.24, conf 95% = 0.22 5 Q 5
0.26). Race did not have a large impact on career aspirations either directly or indirectly.
The direct relationship between race and career aspirations was -.04 with black students
having higher aspirations than white students as noted in Figure 1. The indirect effect of
race on career aspirations through socioeconomic status was also small. This was computed
by multiplying the two path coefficients of each link between race and SES and SES and
career aspirations (0.24 * 0.24), which yielded a positive path coefficient of 0.06
suggesting that white students had slightly higher career aspirations when socioeconomic
status remains in the equation. Therefore, race was not found as a strong predictor of
career aspirations, although black students were found to have slightly higher aspirations
when the socioeconomic class “playing field” was leveled by removing the effect of SES,
but white students had slighter higher aspirations when socioeconomic status was
considered. Overall, SES rather than race, determined the level of career aspirations of the
children in this study, highlighting the need for more multidimensional studies instead of

the univariate analyses that dominate this field of study.

Family Influences on Children’s Career Aspirations

 

Families may provide direct or indirect influences on children’s career aspirations.

The family is an important contextual variable for children’s development in the ecological

43

paradigm. The family is viewed as a micro-system in which a child develops, providing
direct influences on the child and mediating influences of the broader world
(Bronfenbrenner, 1977). Through socialization influences or through the transmission of
human capital resources parents are expected to transmit their resources and values to their
children. Therefore, children might be expected to have similar attitudes to their parents on
key variables related to the development of career aspirations. Such variables of self-
competence and academic achievement have been identified as important predictors of
children’s career aspirations.

Methods of influence

 

Parents may influence their children’s career aspirations through socialization or the
transmission of human capital resources and values. Socialization is an important process
by which children are influenced (Barber & Eccles, 1992). Through this social learning
process children learn by imitating the people they observe in their social environment and
they observe the rewards associated with particular behaviors that are modeled (Bandura,
1971). Within the theory of nested systems (Bronfenbrenner, 1977) there are multiple
layers of influences on children and many people can serve as role models for children.

Such role models may have direct or indirect contact with the children, although
parents are most likely to be the ones who have direct contact with children regarding their
career development (Saltiel, 1985). This influence may be a‘ dynamic reciprocal
relationship rather than a static one-way relationship (Middleton & Loughead, 1993) as
children’s characteristics influence maternal employment and labor force participation
(Galambos & Lerner, 1987), and such labor force involvement may have impacts on

children.

 

 

 

 

 

 

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46

Parents’ labor force activities can shape values and influence parents’ approaches to
their children’s career development. Parents promote skills for their children based on
parents’ perceptions of what is needed in their own job. Parents with blue collar jobs stress
conformity to rules in their parenting, while parents with professional or managerial jobs
emphasize initiative and independence for their children (Hoffman, 1988). By stressing
these values in the home, parents attempt to prepare their children for the world of work
based on their personal experiences. Parent job experiences may also influence the types of
skills that are reinforced in their children. Through their remarks or comments, parents
make suggestions of what types of careers the child might be good at or they may suggest
career ideas, and the suggestions often reflect the career of the parent (Trice, McClellan, &
Hughes, 1992). Values based on parental workplace experiences can shape children’s
socialization about appropriate careers. Families also transmit cultural values and norms
related to career decision-making such as factors of responsibility and autonomy (Young,

F reisen, & Dillabough, 1991). Through socialization, children acquire values and
expectations for success within various roles. These values and expectations are related to
the careers and education that children aspire to achieve (Eccles, 1987). However, these
socialization processes may also be mediated by gender. Behaviors and attitudes toward
work have been shown to be transmitted integenerationally from single mothers to their
children, particularly to their daughters (Shapiro & Crowley, 1982; Waite & Berryman,
1985). Females may be more reliant on role models and family support than males, and
females may be more influenced by their role models than males (Monaco & Gaier, 1992).
Through parental socialization, males and particularly females may mirror their parent’s

attitudes toward work, careers, education, and self-competence. In addition to transmitting

47

values, parents’ may also transmit resources based on their education, jobs, or
psychological resources.

Parent human and social capital resources may provide resources to foster greater
achievement and career goals for their children. Parent educational levels may indirectly
influence children’s career development through the enhancement of their cognitive
abilities (Marjoribanks, 1993b; Moore, Zaslow, Coiro, & Miller, 1996). Higher parent
educational levels have consistently predicted children’s continuity in the labor market
(Parcel & Menaghan, 1994). Parent education has also been related to their children being
less reliant on public assistance (Bane & Ellwood, 1994). Mother’s influences may be
particularly important. Among 16 year old Anglo-Australian and Greek students, mother’s
support of their children’s educational endeavors was strongly correlated with the
educational and occupational aspirations of their children although father’s influence was
not significant (Marjoribanks, 1993a). Parents, and perhaps particularly mothers, can
influence children’s aspirations and decisions through direct and indirect socialization and

transmission of human capital resources such as educational and occupational backgrounds.

Parental Education

 

In addition to transmitting values toward education, parents may also influence
their children’s career aspirations through the transmission of education capital. Parent’s
educational achievements were small to moderate predictors of desired careers and strong
predictors of career expectations (See Table 8). The education level required for the
careers desired by rural 8‘h grade students were moderately related to their parent’s

educational achievement (Sarigiani, Wilson, Petersen, & Vicary, 1990). Similarly, a

48

strong relationship was found between the desire to attend university and parents’
completion of university among 9th to 12th grade females from private schools (Maxwell &
Maxwell, 1994). Benbow, Arjmand, & Walberg (1991) also found a small but positive
relationship between parents’ education and occupational resources and the career
aspirations of their 18-year-old children. The educational attainment of parents was
significantly related to educational level of career aspirations held by adolescents from both
rural and suburban areas. Although these studies on focused on children in 8th grade or
older and did focus on children in economic disadvantage, these studies indicated that,
either through direct intervention or socialization processes, parents’ educational
background influences the career aspirations and performance of their children.

Parental Employment

 

Parent’s employment has been found to impact the career aspirations of children.
Socialization may be an influencing factor since children have expressed career aspirations
similar to those of their parents, especially mothers (See Table 9). Among kindergarten
through 6th grade students, 33% to 40% of girls and 28% to 30% of boys expressed a desire
to have a career similar to their mothers which are rates greater than the 16.7% rate
expected by chance (Trice, Hughes, Odom, Woods, & McClellan, 1995; Trice & Knapp,
1991). The career plans of females were also strongly correlated to the career decisions of
their mothers. The career plans of 8th grade girls to work outside of the home or stay home
with children were similar to their mother’s choice of working versus homemaking (Post,
Williams, & Brubaker, 1996). Children also expressed interest in their father’s careers,
although the rate was lower. Among boys, 12% to 19% aspired to careers similar to their

fathers and 5% to 16% of girls desired careers similar to their fathers (Trice, et al, 1995;

49

 

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53

Trice & Knapp, 1991). Children, especially girls, were influenced by the careers of their
parents. Mother’s careers appeared to be more influential than father’s careers. This may
have resulted from children having visited mothers’ work sites more often than fathers’
work sites and having more awareness of mothers’ employment (Trice & Knapp, 1991).
Although these studies did not specifically focus on the earning potential or socioeconomic
status of children’s career aspirations, they did indicate that the type of jobs held by parents
is an important indicator for the type of jobs children aspire to achieve.

Parent’s employment may also be a source of human or social capital resources that
may influence children’s exposure, access, and aspiration to higher level careers (See Table
10). The socioeconomic status of parents, primarily determined by job type, generally
influenced the education or earning level of career aspirations for children across all age
groups. For children as young as 8 to 11 years old, their socioeconomic (SES) status had a
moderate influence on their career aspirations. Children from higher socioeconomic status
families aspired to careers requiring higher education levels than children from lower SES
families (Phipps, 1995). Higher SES children also tended to be interested in careers for
reasons of personal interest or altruism. Lower SES children were more likely to select a
career based on income potential or the desire to be like a family member or other adult
role model (Phipps, 1995). Family SES background also had a strong influence on the
status of careers desired by 8th grade students. In a path analysis of Solorzano’s (1992) data
(See Figure l earlier), socioeconomic status had a large correlation to the status of careers
that the 8th grade students aspired to achieve. The influence of SES was the strongest

variable in the model, having a stronger effect on career aspirations than race or gender.

54

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55

Students from higher SES families were more likely to aspire to professional careers while
students from lower SES families were more likely to aspire to low-level careers.
Similarly, among 8th grade females, SES was a strong indicator of the choice to pursue high
status jobs in science or engineering careers over homemaking careers (Mau, Dominick, &
Ellsworth, 1995). The effect of class, in combination with age, gender, and ethnicity, also
had a strong influence on the prestige level of careers desired by older students. Among 16
year Australian students, a higher social standing was positively correlated with higher
status careers (Marjoribanks, 1991a). This influence of SES may be moderated by gender
and social conditions.

For twelfth grade students in Canada during a time of high unemployment, SES
was found to have a small impact on the quality of occupational aspirations which may
have been due to the declining economic conditions during the time of the study (Empson-
Warner & Krahn, 1992). Furthermore, this weak effect was moderated by gender. For
females there was a slightly negative impact of SES on aspirations and for males the effect
was positive but extremely small. Overall, the socioeconomic status of parents’ jobs had a
positive effect on the status of careers desired by children. This demonstrates the
significance of the gap in aspirations between lower SES and higher SES children which
has been shown to become even more disparate among as students get older (Jacobs,
Karen, & McClelland, 1991) persisting beyond high school (Gottfredson, 1981). Over time
the career hopes of children from lower SES backgrounds decline, while the career dreams
of children from higher SES backgrounds increase. Although these studies did not examine
parent SES in the context of other predictors of career aspirations, these studies point to

importance of studying the effects of poverty on career aspirations of children. Poverty is a

56

critical factor in determining children’s career aspirations in both the short- and long-term
view since childhood career choices are central to economic empowerment as adults.
Furthermore, economic conditions may moderate the influence of SES suggesting that
community level factors must also be examined in the development of career aspirations,

particularly since poverty tends to be geographically concentrated.

Parental Self-Concept

 

Although no qualitative studies have directly linked parent self-concept with
children’s career aspirations, the psychological resources of the parent and family have
contributed to general career planning. In a study among 11th grade students, family
functioning, as measured by the quality of relationships and organization style of family,
was a better predictor of career development (e. g., taking an active planning role, making
specific career choices) than either gender or parental socioeconomic status (Penick &
Jepsen, 1992). Researchers found that the process of developing certainty of career choices
was enhanced by the existence of an expressive, authoritarian family and was negatively
related to family conflict, and a family organizational style that was democratic, enmeshed,
and idealized. Conversely, they found that taking an active role in career planning as a
student was predicted by a democratic family style that was sociable and disengaged.
Parents’ support, encouragement, and interest in children’s general well being and
educational outcomes was significantly related to the occupational aspirations (both ideal
and expected) of their 16-year old children (Marjoribanks, 1991 a). Parent-child
relationships were important for the career development of older students as well. Among

20 year old male and female students, the strength of the relationship between parent and

57

child was significantly related to the students’ occupational aspirations (Marjoribanks,
1991b).

Family functioning is important to the career development of males. In a
longitudinal study of males from rural economically deprived school districts, Jackson
(1981) studied how the quality of father-son relationships and influenced the father’s role
in their son’s career development. Ten years afier high school graduation differences in F
educational attainment were found for males based on their identification with their father. ‘

Males highly identifying with their fathers achieved significantly higher occupational and I

 

educational attainments than the males with lower identification with their fathers. A

 

strong relationship with fathers is important for the career attainments of males.

This attachment to parents is also important for females’ career development.
Adolescent women with moderate parental attachments were found to have self-efficacy
beliefs and career beliefs that were strongly congruent with their parents (O’Brien &
Fassinger, 1993). However, in another study, the quality of the relationship between high
school senior girls and their parents was not related to the students’ career aspirations. In
general, these female students did not differ in their goals to become leaders in their
profession regardless of their psychological attachment or independence (functional,
attitudinal, emotional, conflictual) fiom their mother or father. The only exception was that
girls who had attitudinal independence from their mothers had significantly lower
aspirations (O’Brien, 1996). Parental attachment may be related to career self-efficacy
beliefs among female children, although it may not be strongly related to actual career

attainment.

58

Community Influences on Children’s Career Aspirations

Ecological theory suggests that children are influenced by the communities that
surround them as they develop. Families transmit human capital resources, cultural values
and norms related to career decision-making (Young, Freisen, & Dillabough, 1991) and
these resources may vary within communities with different socioeconomic backgrounds.
Therefore, the community and family economic variables may create boundaries of
expectations or social norms regarding they types of careers that are possible. While few
studies empirically examine the relationship between community characteristics and

childhood career aspirations, many researchers have indirectly ascertained that community

 

attributes may be influential for a variety of reasons.

Career aspirations moderated by exposure to people and iobs in the community

Children’s exposure to people’s jobs in the community may influence their
aspirations. Children’s aspirations are influenced by observing parents and other adults’
and report knowing someone personally who has the career they desire (Saltiel, 1985;
Trice, Hughes, Odom, Woods, & McClellan, 1995). Media role models were not reported
as an influence on career aspirations, although futtu'e research may be needed to assess the
impact of intemet access to children’s career aspirations. Therefore, the types of jobs that
are held by members of the child’s community may be important in shaping career plans
because children have direct or indirect knowledge of their work because of their visibility
and accessability. Evans & Herr (1994) reported that young adults’ career aspirations were
ofien limited to those jobs that served or were supported by their own ethnic community.
Those pe0ple that children have the most contact with are likely to shape children’s career

ideas. Because poverty tends to be geographically located in areas with distressed

59

economic climates (LaMore, 1993), children living in poverty may have limited exposure
to careers with economically self-sufficient wages.

Career aspirations moderated by community type

Communities with a narrow range of occupations may provide a limited range of
role models and that may inhibit the career aspirations of the local children. Because of
their size and opportunities, rural, urban, and suburban communities may offer different F
types of role models. Trice (1990) found that children from rural and urban environments
showed a restricted range of career interests as they were more likely than suburban

children to choose the careers of their parents (Trice & Knapp, 1991). Hall, Kelly, & Van

 

Buren (1995) found that students from rural school districts had a narrower range of career
interests than urban youth and that the jobs preferred by rural students tended to pay less
than the jobs preferred by the urban adolescents (See Table 11). For example, the urban
students were more likely than rural students in 8th and 11th grades to aspire to artistic
careers and social careers. Among 8th graders, rural students were more likely to desire
investigative careers while urban student had higher interests in investigative careers in the
11th grade sample. Because of the potential varied role models in urban areas, students
from urban areas may have a greater range of career interests than rural students. The
effect of the community type may also be moderated by individual differences. Hall,
Kelly, & Van Buren (1995) found a significant, but small, effect of a gender by community
interaction on career preferences. They found that males fiom rural settings were more
interested in realistic careers than all other students. Rural females were less differentiated
in their career aspirations than urban female and rural males, and rural females had higher

realistic career aspirations than males and females in urban settings. These differences in

career aspirations of students fiom different types of communities may be linked to lack of
exposure to these careers in rural communities or to differences in educational
programming. This limitation may be even greater for students from rural areas that are
geographically isolated from other communities, or for children from economically
distressed communities. Although these studies only focused on the differences between

rural and urban communities and did not consider economic disadvantage, these studies W

suggest that community characteristics are important.

Career aspirations moderated by community economic conditions

 

Economic opportunities and the local job market may be a very strong factor in
limiting youth’s career choices. Roberts (1968) has argued that the local opportunity
structures strongly impact the career decisions of students as they make the transition from
school to work. According to Gottfredson’s (1981) theory of vocational development,
children become socialized to vocational expectations regarding power, sex-typing, and
social valuations of careers. According to this theory, by the time children reach 14-18
years of age, they have integrated their own interests with possible occupational choices.
However, the influence of local opportunities may be a stronger force than individual
preferences.

Hall, Kelly, & Van Buren, (1995) found that adolescents may be more likely to
select career choices based on occupational opportunities in the local job market, rather
than based on personal interests. This reflects an awareness of the local possibilities and an
attempt to fit within those parameters. Furthermore, Furlong & Cartrnel (1995) found that
13-year old students expressed a much wider range of desired careers than expected

careers. The authors surmised that the narrow range of careers that children expected to

61

achieve were constrained by the jobs that they perceived were available in their own
community. Furlong & Cartrnel (1995) also reported a significant but small to moderate
effect of the community economic conditions on career aspirations and expectations (See
Table 12). Community conditions had a small direct effect on aspirations Q = 0.05) and a
moderate effect on females career expectations (r = 0.07). Community conditions had a
small direct impact on both career aspirations (r = 0.05) and expectations (3 = 0.03) of
males. The economic stresses in the region may also limit youth’s abilities to select jobs
that match their aspirations. Upon observing the declining opportunities in the local job
market due to the farm crisis, Van Hook (1990) found that adolescents were also forced to
consider economic opportunities outside of the local community. In this study, the
majority of students in these economically distressed rural areas reported a desire to further
their education to ensure their success beyond the limited labor market opportunities in
their home community. In other communities the jobs preferred by rural students were also
incongruent with forecasts of future job openings (Hall, Kelly, & Van Buren, 1995).
Empson-Warner & Krahn (1992) also found that the aspirations of youth were greater than
what was presently available in their current economy. This mismatch was also found
among younger students as well. Phipps (1995) observed a poor fit between the
occupational aspirations of 8 to 11 year olds and the availability of jobs in those
occupations. The level of interest in artistic and investigative careers was higher than the
level of employment available in that field. Conversely, students were aspired to
enterprising jobs less than the actual rate of employment in that area. There appears to be a
mismatch between student’s desired occupations and the types of occupations available

locally, especially in economically distressed communities as student career exceed the

62

 

local opportunities. The limited job market in these distressed communities leaves youth in
a difficult place of choosing better career possibilities versus staying near important social
ties resides (Elder, King, & Conger, 1996) so some youth may adjust their career
expectations to fit the local job market. Although there is a very limited number of

empirical studies on the relationship between community economic conditions and the

 

 

economic status of children’s career aspirations, these studies suggest that the relationship I”
is important and warrants further consideration.

Community economic conditions limit educational plans

In addition to limited career aspirations, community economic conditions can also h

influence educational plans required for different careers (See Table 12). Furlong &
Cartrnel (1995) researched the career and educational aspirations and expectations of youth
from three communities with varying economic conditions. A strong correlation Q = .26)
was found between the economic health of the community and the desire of these 13-year
old students to attend university after graduation. Youth from the economically depressed
city were significantly less likely to expect to attend university than students from the more
prosperous communities. Similarly, Sarigiani, Wilson, Petersen, & Vicary (1990) found
that students from the suburban community (high income") were much more likely than
students from the rural community (low incomes) to have educational plans beyond high
school. Aspiring to fewer years of education may leave youth with fewer career choices
and opportunities for increased earnings. Children living in economical distressed regions

are at risk for having lowered educational and career aspirations. The level of economic

 

’ 1980 median family income was $42,600 to $55,657
5 1980 median family income was $14,500

63

distress in the community appears to influence the general educational and career
aspirations of the children in the community (Furlong & Cartrnel, 1995; Sarigiani, Wilson,
Petersen, & Vicary, 1990). However, it is not clear how much of this is attributed to the
socioeconomic background of the family or the community, since the socioeconomic status
of the community mirrors that of many families within the area. It may be possible that
family social class may moderate the influence economic distress.

Aspirations moderated by experience in the communiflver time

Children’s desired careers may be influenced by exposure to conditions within the
community. The careers that children actually expect to achieve may be further limited by
exposure to the local career opportunities over time. Young adult career aspirations have
been found to decline in the year following graduation for those students who experience
unemployment after graduation (Empson-Warner & Krahn, 1992). Childhood career
aspirations may also decline as they discover that there are not as many high-status jobs
available to fill the demand (Jacobs, Karen, & McClelland, 1991). However, aspirations
may also be expanded as youth enter the labor market. In their study of the effects of sex-
typing on career aspirations, Levine & Zimmerman (1995) concluded that the labor market
conditions were probably more predictive of the occupational achievements than their
career desires expressed during high school. The jobs that women held in their twenty’s
did not appear to be limited by the sex-stereotyping of their earlier aspirations, and this

mobility actually increased as they spent more time in the labor force.

 

 

 

 

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67

Summa_ry

The community economy is an exosystem variable in the nested systems model
(Bronfenbrenner, 1977) that influences the career aspirations of children. Children may be
directly influenced by the local job market because they shape their expectations to fit the
available jobs. Children may also be indirectly influenced by the community economy
through socialization. Family, friends, and other role models may transmit their own values
about career possibilities to the youth. Furthermore, the conditions of the distressed
economy may provide inferior educational opportunities that may indirectly limit
children’s aspirations for the future. Therefore, role modeling, socialization of norms, and
availability of resources may directly and indirectly limit the career aspirations of children.
Summary of expected effect sizes

Based on the literature review for these various ecological influences on career
aspirations, several meta-analyses were conducted to determine the expected effect sizes
for individual correlations between selected variables using the data presented in the tables
contained in the literature review. Bare bones meta-analyses were conducted using
procedures outlined by Hunter, Schmidt, & Jackson (1982). Correlations were not
corrected for artifacts (e.g., reliability, restriction of range, etc). Multiple correlations were
allowed per study when different results were presented by age, gender, or other subgroup
analysis.

Table 13 shows the results of these meta-analyses. The number of study
correlations used in each meta-analysis is indicated by k. The total number of people
included in those samples used in the correlations are indicated by n. Rho, indicated by P,

is the estimated mean population correlation of the relationship between the study

68

variables. The 95% confidence intervals provide an indication where the range of the
population correlation would be expected to be found 95 times out of 100. Thus, mean rho
statistics with 95% confidence intervals entirely above or below zero are significant at the p
< 0.05 level and are indicated by the asterisk. Variance in the sample is indicated by Vr
and variance attributed to error is indicated by Ve and are effects not attributed to the true
relationship between the study variables. The percent of variance in an indication of how
much of the dependent variable is accounted for by the independent variable.

Based on these results of the mean population correlation and the range expected
for those correlations 95% of the time, it can be noted that the individual demographic
variables of age, race, and gender did not have a consistent relationship to childhood career
aspirations. However, there was a strong relationship between children’s grades and self-
competence that positively predicted higher career aspirations. Similarly, parents
educational and job or socioeconomic status were also strong in positively predicting
higher career aspirations. Differential among community types were also strong in
predicting different levels of career aspirations. These findings suggest career decisions
may be impacted more profomdly by external resources and forces outside of the
individual than by individual characteristics or demographics. It further provides support
for the exploration of these relevant human capital variables related to children, families,

and communities that can impact children’s career aspirations.

69

 

 

 

 

 

 

 

 

 

 

 

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Chapter 3 Model and Hypotheses
Research Focus
The previous literature review documented the strength of various human capital
resources in directly predicting children’s career aspirations. The present research will test
the hypothesis that these human capital variables will be transmitted from the community,
to the family, to the child according to the nested systems ecological theory
(Bronfenbrenner, 1977). An overview of this proposed model is provided in Figure 3 and

described in more detail following the figure.

 

 

 

 

 

 

 

HUMAN ECOLOGICAL LEVEL
CAPITAL TYPE I Community I Mother I Child I
Psychological Self- __, Self-
Competence Competence
Education Educational Educational Academic
Attainment._+ Attainment I Achievement I
(Mean)
Employment Job Job Career
Socioeconomic Socioeconomic Aspirations
Status —-—> Status + (Socio-
(Mean) economic
Status)
I Baseline I Time 1 Phone Interview I

 

Figure 3 Proposed Ecological Structural Equation Model

71

Overview of the Research Model

As shown in Figure 3, community capital is predicted to positively impact
mother capital which is predicted to positively effect child capital and career aspirations. It
is expected that this flow of capital will occur across the domains of psychological,
educational, and employment domains. First, it is assumed that psychological resources
will be positively transmitted from the mother to the child. It is expected that mothers’
level of perceived self-competence related to their lives and jobs will be reflected in
children’s perceived self-competence related to their self-worth and abilities and would
positively predict the quality of jobs that they aspire to achieve. Second, it is assumed that
the macro-level variable of the average community educational attainment will impact
mother’s level of educational attainment. The highest level of education that mother’s have
achieved is expected to contribute positively to the type of grades children receive in their
basic courses at school. This level of children’s academic achievement is expected to
positively impact the quality of jobs children aspire to achieve. Third, it is expected that the
macro-level variable of the average socioeconomic status of jobs held by community
members will positively impact the socioeconomic status of the job currently or most
recently held by the mothers. The socioeconomic status of the mothers’ jobs is expected to
positively relate to positively impact the socioeconomic status of the jobs children aspire to

achieve.

Hypotheses and Planned Analyses
Two types of analyses will be used in the present research, including a structural

equation model followed by t-tests and ANOVA’s to detect potential group differences.

The first analysis, a structural equation model, will test an ecological model integrating
existing literature. This ecological model shown in Figure 4 will test the assumption that
influences on children’s career aspirations are indirectly influenced by mother and
community capital. Although ecological and system dynamic theories suggest that these
influences may be bi-directional (Lerner & Lerner, 1986; Levine & Fitzgerald, 1992), the
model to be tested includes only unidirectional hypotheses. The hypotheses associated with
model are as follows:

Community capital influences on mother capital

1. The average level of the educational attainment of the mother’s community will

 

positively predict mother’s educational attainment level.

2. The average socioeconomic status of jobs held by residents of the mother’s
community level of the educational attainment of the mother’s community will
positively predict the socioeconomic status of the mother’s current or most
recent job.

Mother capital influences on children

 

3. Mother’s level of self-competence will positively predict children’s level of
self-competence.

4. Mother’s level of educational attainment will positively predict child’s
academic achievement.

5. The socioeconomic status of the mother’s current or most recent job will
positively predict the socioeconomic status of children’s desired and expected

career aspirations.

73

Children’s resources influencing career agirations

6.

7.

Children’s desired jobs will predicted their expected jobs.

Children’s self-competence levels will positively predict the socioeconomic
status of their desired and expected career aspirations.

Children’s reports and mother’s reports of children’s grades will be similar.
Children’s academic achievement scores (rated by both mother and child) will
positively predict the socioeconomic status of their desired and career

aspirations.

A second set of analyses will use t-tests and analyses of variance to determine

whether or not child demographic characteristics influence the career aspirations of

children. This is an important consideration for understanding any potential differences

based on key measures of diversity. The research questions to be addressed in this model

include the following:

10. Do the socioeconomic status of children’s career aspirations significantly vary

between males and females?

11. Do the socioeconomic status of children’s career aspirations significantly vary

between black and white children?

12. Do the socioeconomic status of children’s career aspirations significantly vary

by grade levels?

13. Do the socioeconomic status of children’s career aspirations significantly vary

by age groups?

74

 

Usefulness of a Path ModelingApproach in Testing Competing Theories

 

The equationpath model(SEM) is useful for a variety of reasons. First, it allows the
effect of variables to be considered in the context of their relationships to other variables.
Single relationships between variables may change in the presence of other variables in the
model. Therefore, path modeling is appropriate for studying an ecological model that seeks
to understand a social problem in its context. By including these multilevel influences fiom
the family and community this model will also test the usefulness of taking a structural I

approach, rather than an individual approach, to the development of career aspirations

 

among low-income children. Such a model may be helpful in addressing issues related to
the intergenerational transnrission of poverty and other long-term implications of career
planning for children receiving public assistance. This is particularly important because
traditional research has overlooked the career development of low-income individuals
(Kossek, Huber-Yoder, Castellino,& Lerner, 1997) and the stress of poverty may create
additional obstacles to children's career development that may not be experienced by other
populations (Connell, Aber, Walker, 1995). Therefore, researchers must understand how
the important tasks of career development occur during childhood and adolescence, and are
influenced by multiple factors within the child, family, and broader community over time
and whether these influences are direct or indirect.

Secondly, the path modeling approach is useful for identifying the best model of
alternative models. Using path-modeling sofiware (Hunter & Hamilton, 1995) all possible
links between variables in the model are analyzed to determine which links should be
added or deleted to create the best fit. Therefore, the proposed model will be analyzed

using goodness of fit indices and individual link analyses to determine whether any links

75

should be added or deleted to increase the overall fit in the final model. Through these
model-fitting exercises the best model of all possible models using these variables will be
identified, regardless of whether it was hypothesized or not. For example, even though
community and family variables are proposed to be indirectly related to children’s career
aspirations, fiom these exercises one can determine whether the model would be a better fit

if community or family human capital resources were directly linked to career aspirations, F

rather than indirectly linked as hypothesized. Furthermore, one can also determine whether
the individual or structural approach is a better fit by examining which paths should remain

in the model since non-significant variables will be elirrrinated in the final model. Such

fan—n.- .1 Twi.

model-fitting exercises will test the relative importance of community, family, and child
variables in the full model and only those variables meeting a threshold of statistical
importance will be retained in the final model. Through the use of the path modeling
approach, these variables will be studied in relationship to their broader context and will

provide feedback for structuring the most appropriate models.

Justification for Hypotheses for Human Capital Transmission Across Ecological Levels
The previous literature review documented the need to integrate child, family, and
community level predictors of childhood career aspirations. A meta-analysis of the
existing research suggests that human capital variables of edtrcation, employment, and
psychological resources were significant predictors of children’s career aspirations at
various levels (child, family, community). These influences have been tested as direct

effects on children’s career aspirations, however, human capital theory and the ecological

76

 

perspective suggest that these resources may be transmitted indirectly from the community
to the family and then to the child.

In human capital theory, Becker (1964) describes skills and knowledge as essential
assets for advancing individual potential. Investments in these skills and knowledge are
made with an expectation of a retrun on these investments. Education and employment are
considered basic human capital investments, although Marjoribanks (1991b) expanded r
human capital theory to include psychological attributes as well. These assets reside within

individuals, families, and communities. The connection between these individual, family,

 

and community levels are important for advancement. Coleman (1988) stated that the
relationship between people and social structures provided for the development of human
capital. Tangible and intangible assistance are exchanged through a system of mutual
expectation and obligation in which members of the social structure share trust,
information, and social norms. Through these structures people can gain access to
influential others, information, financial assistance, and other resources to help them
advance. The community and the family are social structures that contain human capital
assets that could help children advance their career opportunities by investing their assets in
the child.

Transmission from Parent to Child

 

Therefore, children may advance their career aspirations by drawing upon the
human capital resources of their parents. Families transrrrit human capital resources,
cultural values and norms related to career decision-making (Young, Freisen, &
Dillabough, 1991). Parents may provide resources such as information about a particular

career, access to employers who may hire them, access to influential people to recommend

77

 

their admission to college, or parents may even teach their children particular vocational
skills. Parental influence may be transmitted by other mechanisms as well. Children may
also become socialized by the norms and expectations of their parents (Barber & Eccles,
1992) so that their expectations for future jobs and educational plans may mirror what their

parents have done themselves, or what they expect their children to do. Children may also

 

be influenced through the social learning process in which they shape their career related Ir
behaviors by observing parental behavior and the rewards associated with their behavior, '
and then by imitating their parents (Bandura, 1971). Through this process, children may {I
develop particular patterns of behavior similar to their parents, such as reading instead of h

watching television, taking up sports or hobbies, or developing social skills in ways that
will better prepare them for some careers over others. In general, the link between the
nested system levels of parent and child may be explained in several ways, including social
capital, socialization, and social learning.

Transmission from Community to Parent and Child

 

The link between the human capital variables in the community and family levels
may also be explained in a similar fashion. Human capital resources present in the
community can influence the human capital development of parents through exchanges
between people and social structures as in the development of social capital. The
employment and education characteristics of a community can be an indication of what
types of jobs and education types are expected among residents. Parents can be socialized
to these expectations which can then be transnritted to their children, and children can be

directly socialized by these community expectations as well.

78

However, actual opportunities, rather than socialization, may determine the level of
human capital available for local residents. Characteristics of the local community may be
a reflection of the health of the local economy which local community characteristics The
economic base of the community can shape the amount of human capital assets available
for investment in the parents’ careers. The economic characteristics of the community can
be indications of the quality of employment and educational opportunities available locally.

The local opportunity structure determines the actual career development (in terms of the
quality of employment, education, and earnings available locally) for local parents and
children (Blakely, 1994) depending on how far they are willing to go or able to seek non-
local opportunities (Lyons & Hamlin, 1991), although discrimination has systematically
prevented people from accessing employment outside their distressed communities
(Turner, 1997). Because poverty is concentrated in geographic areas and associated with
poor employment and education opportunities due to cyclical disinvestrnent (Wilson,
1996), the overall human capital resources of employment and education residing in
individuals and social structures may be lower in areas of poverty. Therefore, parents may
have access to fewer resources to advance their own career progression, which in turn
provides them with fewer resources to transmit to their children. Children’s own career
aspirations may also be directly affected by the lack of resources in their community due to
diminished educational opportunities or summer/after-school job experiences that would
prepare them for career advancement. The availability of human capital assets residing in
the community can influence parents and children directly, and children indirectly through

the parents.

79

 

Justification for Links within the Measurement Model

The transmission of human capital across these levels is an important consideration
for the development of children’s career aspirations. Therefore, key human capital
variables residing with individuals, families, and communities will be assessed within the
nested system model testing the hypothesis that these human capital resources are
transmitted across the ecological levels from community to family to child. These human
capital variables include child self-competence, child academic achievement, quality of
child career aspirations (individual level), mother self-competence, mother academic
achievement, quality of mother employments (family rrricrosystem level), community
education level and community employment earnings (exosystem level). In addition to the
general theoretical rational presented above, specific justification will be provided for the

inclusion of these variables in the measurement model.

Individual Influences

 

Child Self Competence Predicts Child Career Agairations

 

According to the meta-analysis of the literature reviewed in the present research,
children’s level of self-competence is a strong predictor of career aspirations (r = 0.27).
Self-perception has been defined as important in career decision-making (Super, 1957) and
the development of an occupational identity (Erikson, 1963; Marcia, 1980) which are
foundational in the development of career aspirations. More specifically self-efficacy has
been related to aspirations for workplace leadership (O’Brien, 1996; Singer, 1990) and
success (Singer, Stacey, & Lange, 1993) among youth. Such aspirations are an indicator of

concern for setting goals and achieving workplace rewards that may include socioeconomic

80

status of the job. Self-competence, which encompasses a broad defrrrition of self-esteem
for children (Halter, 1982), has been positively related to career exploration and negatively
to career indecision. (Wallace-Broscious, Serafica, & Osipow, 1994). Youth self-esteem
has been related to success (Kawasaki, 1994) and decisiveness in career planning (Chiu,
1990) along with setting high career goals (McCullough, Ashbridge, & Pegg, 1994). Such
career planning and decision-making are keys to evaluating the economic potential of
vocational choices and taking action to prepare for high paying careers (Crawley, & Black
1992; Man, Dominick, Ellsworth, 1995). Therefore, the measurement model employed in
the present research will include a link showing that childhood self-competence will predict
the socioeconomic status of careers preferred during childhood.

Child Academic Performance Predicts Child Career Aspirations

 

According to the meta-analysis of the literature reviewed in the present research,
children’s academic achievement or grades is a strong predictor of career aspirations (r =
0.39). Decision-making skills, reading skills, and cognitive abilities are necessary for
vocational problem solving and planning (Peterson, Sampson, & Reardon, 1991) and
understanding and evaluating career education materials (Billups & Peterson, 1994). These
comprehension and analytical skills are needed for assessing the earning power of various
careers and to adequately prepare for high paying skills by completing advanced education
or training. Students who perceived schoolwork as having a high extrinsic value were
found to have higher career aspirations (Singer, Stacey, & Lange, 1993). These skills,
motivations, and abilities may be reflected in student grades and other academic measures.

Measures of academic performance and potential may be indicators of ability to

pursue and succeed in the education or training needed for high quality jobs. Standardized

81

achievement scores were positively related active career planning, although not directly
related to selecting a particular career (Penick & Jepsen, 1992). Academic achievement
was strongly related to occupational aspirations (Empson-Warner & Krahn, 1992; Man,
Dominick, Ellsworth, 1995) and very strongly related to educational aspirations (Mau,
Dominick, Ellsworth, 1995) that may be needed for employment in jobs with high levels of
socioeconomic status. Students experiencing success in the school setting appear to be on
the course for economic success in the workplace. Conversely, academic failure or
disadvantage is associated with lowered career aspirations (Rojewski, 1995). In the
proposed measurement model, childhood grades will be used to predict the socioeconomic

status of preferred childhood careers.

Family (Maternal) Influences6

 

The family rrricrosystem is considered to be a primary and direct influence on
children’s development within the ecological framework (Bronfenbrenner, 1977; Lerner &
Lerner, 1986). Social learning theory suggests that this influence is a result of
socialization (Barber & Eccles, 1992). Children learn by imitating the people they observe
in their social environment and they observe the rewards associated with particular

behaviors that are modeled (Bandura, 1971). While the role models may be direct or

 

6 Because of the high number of low-income children living in single female-
headed households, family influences will focus on mothers in the measurement model. In
addition, maternal support has been shown to be stronger than paternal support in

predicting career aspirations (Marjoribanks, 1993a).

82

indirect contact with the children, it is parents who are most likely to have sustained direct
involvement with their children (Saltiel, 1985) and are more influential career role models
than other adults known to the child (Trice, Hughes, Odom, Woods, & McClellan, 1995).
In addition to socialization processes, families may influence career aspirations through the
transmission of human capital resources, cultural values and norms related to career
decision-making (Young, Freisen, & Dillabough, 1991). The availability of skills and
resources may determine a child’s preparation and ability to pursue high quality
employment.

Mother Self-Competence Predicts Child Self-Competence

Through this socialization process, children may adopt patterns of behavior that are
similar to their parents by observing their actions. Since children’s self-competence was
found to be a significant predictor of career aspirations in the meta-analysis of the literature
reviewed (r = 0.27) and children have attitudes and perceptions similar to their parents, a
portion of children’s self-competence may be traced to their parents. For instance,
adolescent women with moderate parental attachments were found to have self-efficacy
beliefs and career beliefs that were strongly congruent with their parents (O’Brien &
Fassinger, 1993). Children of both sexes tend to be congruent with their parents on values
(Rozin, 1991) and employment attitudes (Eccles, 1987; Starrels, 1992). These career
related behaviors and attitudes have been shown to be trarrsrriitted integenerationally from
single mothers to their children, particularly daughters (Shapiro & Crowley, 1982; Waite &
Berryman, 1985).

Parents may be additionally influential in the development of self-competence

attitudes through reinforcement, since childhood self-concepts are not yet finalized (Rutter,

83

1992). And because parents and children are mutually reinforcing to one another (Lerner
& Lerner, 1986; Middleton & Loughead, 1993), parents and children may begin to develop
similar patterns of self-competence beliefs based on their behaviors toward one another.
For these reasons, a link will be proposed in the measurement model showing a direct
relationship between maternal self-competence attitudes and the self-competence attitudes
of the children as an indirect predictor of child career aspirations.

Mother Academic Performance Predicts Child Academic Performance

In the present review, parents’ educational attainment was related to children’s
educational aspirations (Maxwell & Maxwell, 1994; Sarigiani, Lee Wilson, Petersen, &
Vicary, 1990), continuity in the labor market (Parcel & Menaghan, 1994), and decreased
reliance on public assistance (Bane & Ellwood, 1994). Social learning theory suggests that
mothers and their children would share similar characteristics in their academic
performance. A higher level of educational attainment implies higher level of academic
achievement needed to successfully complete the additional educational requirements
beyond high school. Through socialization and observation, children may learn to imitate
their parents’ beliefs about the importance of schoolwork or study-related behavior (e. g.,
reading versus watching television). In addition, human capital theory (Becker, 1964)
suggests that important resources are passed from parent to child. Mothers’ academic
performance history could include many of the resources that parents have to transmit to
their children, including content knowledge, ability to acquire information, knowledge of
the educational system, comfort talking with educators, etc. Parental education has
contributed to the cognitive abilities of children, and their ability to cope with poverty

(Moore, Zaslow, Coiro, & Miller, 1996), leading to the increased chances that students will

be successful in school. Mothers’ past grades can be an indicator of the level of these
resources she has to contribute to her child’s education. Therefore, the proposed
measurement model will indicate that mothers’ educational level will predict the grades of
the children, indirectly influencing career aspirations.

Socioeconomic Status of Mother’s Job Predicts Socioeconomic Status of Child’s
Desired Job

Socialization influences, described earlier, are expected to result in similarities in
career preferences between mother and child. Children’s career preferences tend to mirror
their parents. Vocational aspirations of children have been strongly linked to their parents’
actual occupations (Marjoribanks, 1991a; Marjoribanks, 1996; Trice & Knapp, 1991; Trice,
Hughes, Odom, Woods, & McClellan, 1995) and even their parents’ occupational
preferences (Marjoribanks, 1995). Similarity in career choices may also result from the
transmission of human capital through socioeconomic status. Parental employment and
socioeconomic status are important human capital resources that are passed along to
children (Becker, Coleman, 1988; Marjoribanks, 1991b).

Family socioecononric status has been linked to children’s motivation for selecting
a particular career. Children from the lower socioeconomic status group were more likely
to select a career based on income potential or the desire to be like a family member or
other adult role model (Phipps, 1995). Socioeconomic status is also related to career
planning and career certainty (Penick & Jepsen, 1992) which may indicate a stronger
likelihood that career earning potential would be evaluated. Higher socioeconomic status

backgrounds are also linked to students’ choosing academic school programs, which may

85

lead to higher earnings, over non-academic school programs (Empson-Warner, & Krahn,
1992).

Career aspirations have been positively related to the socioeconomic status of the
family (Della Fave, 1974; Man, Dominick, & Ellsworth, 1995; Sewell & Shah, 1968;
Solorzano, 1992). The disparity in aspirations between lower and upper SES students has
increased with age (Jacobs, Karen, & McClelland, 1991) and has persisting even beyond
high school (Gottfredson, 1981). In light of these findings, socioeconomic status of the
mothers’ most recent job is expected to positively relate to the socioeconomic status of the

child’s preferred career.

Communiy Human Capital Predicts Mother Human Capital

 

Bronfenbrenner’s (1977) nested system theory suggests that the influences of the
exosystem are mainly indirect on the individual, and that the rrricrosystem or other social
structures filter the majority of the exosystems’ influences. Therefore, it is hypothesized
that the community level influences will primarily influence the child through the parents.
As discussed earlier, the employment and educational resources residing in the community
residents and social structures may influence the development of individual employment
and educational assets (Coleman, 1988) through the local opportunity structure (Blakely,
1994) or through socialization or social learning processes (Bandura, 1971). The level of
education and employment of local residents may be an indication of what is expected or
what is actually available in terms of college, vocational training, and industry. Therefore,
it is hypothesized that the average level of education found in the community will predict

the education level of mothers, and that the average socioeconomic status of j obs held by

86

community members will predict the socioeconomic status of mother’s most recent job.
These human capital assets of the mothers are expected to predict the human capital assets
of the children, therefore, the influence of the community capital could indirectly influence
children.

Comparisons by Child Demggraphics

Additional analyses will examine children’s background characteristics of age,
gender, and race for any influence on career aspirations. Age will be examined in cross-
sectional analyses and in quasi-longitudinal analyses over a one-year period. Cross-
sectional analyses (AN OVA) will be conducted to determine if there are significant
differences in desired or expected job scores at time 2 by age groups. In addition, the issue
of whether or not the prestige of children’s career aspirations are stable over time will be
addressed by testing for any significant differences between desired or expected job scores
from the beginning of the study to the follow-up interview one year later. Analyses of
variances will also be conducted to determine if desired or expected career aspirations vary
by racial groups since race has been examined as an influence on the career aspirations of
children (Phipps, 1995; Solorzano, 1992) although socioeconomic status may account for
this relationship more directly. In addition, T-tests will be used to determine if desired and
expected career aspirations will be significantly different for‘males and females. Gender
differences have been noted in the types of careers desired and the level of education
desired for jobs, but have not conclusively predicted job prestige as noted in the meta-
analysis of the research reviewed in this paper. This suggests that neither age, gender, nor

race will be directly predictive of prestige scores of career aspirations. However, due to the

87

importance of race, class, and gender in interpreting research outcomes, these variables will

be examined in the present research.

88

Chapter 4 Method
Procedures

A random sample of mother and child pairs was randomly selected from the client
database of the Michigan Family Independence Agency (formerly the Department of Social
services). The sample was drawn from four districts participating in an experimental
program as part of a larger public policy evaluation (see Kossek, Huber-Yoder, Castellino,
& Lerner, 1997). The sample was stratified based on mothers’ level of participation in the
experimental (or control) program. Across the four districts, a random sample of 1188
female clients and a child between the ages of 9 and 13 year was drawn in October of 1993.

To begin the study, clients were contacted with an initial letter from the Director of
the Michigan State Family Independence Agency (MIF IA) explaining the importance of
the program evaluation, and that client information reported in the interviews would not be
given to the MIF IA. Additional letters were sent from the researchers on university
letterhead, reiterating the importance of the study and restating that all interviews would be
kept confidential. Instruction sheets and consent forms were provided with the letters from
the university.

In the instruction, clients were asked to complete the consent form, to provide
phone numbers where they could be reached, and to mail this form back to the University
in the postage-paid reply envelope. Clients with no telephone service were instructed to
call the toll free 800 number at the university and schedule an interview at a time that was
convenient. At least three attempts were made to contact each client if they did not respond
to the first letter. Clients were mailed up to three letters if they did not respond to the first

letter. In addition, 207 clients with telephone numbers available through directory

89

assistance were also contacted by phone to explain the study and obtain verbal consent to
conduct the telephone interview.

Interviews were conducted over the phone by trained interviewers a time and place
convenient to the client. Following the interview with the mother the child was interviewed.
Mothers and children each received $5 for the first completed interview and they each received

$10 for the second interview completed one year later

Sample

Difficulties including clients in the study

 

Surveying this population presented some unique challenges. The client population
was not easy to contact due to address changes and not having a telephone in their
residence. In addition, some of the information requested was highly sensitive (e.g., job
eanrings, presence of other working adults in the household, etc.) and required participants
to trust that researchers would not report income data to the Family Independence Agency.

Consent to conduct the child interview was occasionally denied because mothers did not
want their children to know that their family was receiving public assistance. Overall,
mothers agreed to have their children participate in the study between 70 and 80% of the
time, which was greater than expected. Table 14 below highlights some of the difficulties

in contacting clients for the first interview, and the attempts to include them in the study.

Table 14 Client consent rates in the first interview

 

No response to letters or calls .................... 724
Could not contact by phone ......................... 56
Mail returned due to bad address ................. 32
Refused to participate ................................ 137
Could not complete interview ...................... 26
Completed first interview .......................... 213

TOTAL IN ORIGINAL SAMPLE ......... 1188

 

Sample size

From the initial random sample of 1188 mother-child pairs, 212 mothers and 159
children completed the first interview during the spring and summer of 1994. One year
later, 145 mothers and 104 children of who had completed the first interview also
completed the second interview. For the purpose of the majority of analyses presented in
this paper, a sample size of all 159 mother—child pairs who completed the first interview.
Some children did not answer a few questions and these questions were replaced with the
group mean.

Child Demographics

 

The mean age for the children at the time of the first survey was eleven. 54% of the
children were females, and 46% were males. The race of the children was not assessed in

the telephone survey.

91

Mother Demographics

 

A majority of the sample was either Black/Afiican American or White/Caucasian.
Black respondents comprised 48.8% of the total sample, closely followed by white
respondents who were 41.1% of the sample. The remainder of the sample consisted of
Arab/Chaldeans (4.8%), Hispanic/Latina (1.9%), and Native American (5%) mothers. The
remaining 6% of the sample did not provide ethnic information.

The mean age of the mothers during the first survey was 35. At the time of the first
survey 15% of mothers were married, and 20% were married at the time of the second
interview. In both surveys, the average number of total members living in these
households, was between three and four, and a majority of these people were under age 18.

The mean age of the children living in the household was just under 10 for the first survey,
just over ten for the second survey. In the first interview, 30% of the mothers reported
working full or part time, and 51% reported working full or part time in the second

interview.

Comparing the survey sample of mothers to the random sample of mothers

 

Archival data was available fiom MIFIA for all mothers. This data was used to
compare the survey sample with the random sample on age, race, education, and income.
In these comparisons the two groups were found to be similar on education and ethnicity,
but different in age and earned income.

The respondents were just as likely as the non-respondents to have graduated from
high school (t=-1.63, p=.104) and the ethnicity of both groups was similar. However, the

two groups were significantly different from one another on age (t=29.19, p=.000). The

respondents were older (average=35) than the non-respondents (average=22). The two
groups were also significantly different in the amount of earned income reported prior to
the interviews (t=5.02, p=.000). For the month of February 1994 (the first month of the
mother interviews), the survey respondents reported much higher levels of monthly earned

income (average=$3 66.67) than the non-respondents (M=$182.93).

Measures

Multiple methods of measurement were used throughout this 36-month study.
Community variables were measured using 1990 census data (STF3 zip code file) for the
zip code of clients’ residences at the time the random sample was drawn in January of
1994. This sample was drawn several months prior to the first wave of interviews. Because
the address data and census data pre-date the collection of the survey data, community
variables were considered baseline data Mother and child variables were collected in
subsequent telephone surveys conducted in the following two years. For the path model,
mother and child human capital variables and as well as child career aspirations, were
selected from the interviews conducted in the spring and summer of 1994. For t-test
comparisons child career aspirations data was also used from the follow-up interviews held

in the spring and summer of 1995. More details about these variables are presented below.

Child Career Aspirations

 

The main dependent variables relating to child career aspirations were measured
using two separate items. Children were asked about their desired and intended careers:

"What would you like to be when you grow up?" and "What do you think you will be when

93

you grow up?" These answers were assigned a job number and a corresponding prestige
score using the socioeconomic index revised by Stevens & Cho (1985). This index
assigned scores to the 1980 census occupational titles based on the earnings and education
associated with each occupational title. The “Total Socioeconomic Index” (TSEI)
computes prestige scores based on male and female earnings while previous versions of the
scale based on older economic data were computed using only male earnings. Although
this index used occupational titles from the 1980 census, it was the most current coding
scheme available.

Three trained advanced graduate students used this index to rate the socioeconomic
status of the careers mentioned by children in this study. A reliability analysis was
conducting to measure the similarity of the socioeconomic statuses assigned by the 3 raters.

The inter-rater reliabilities for the socioeconomic status of the careers reported by children
in the second survey were as follows: Desired job (gr—.98 survey 1; r=.99 survey 2);
Expected Job (gr-.97 survey 1; r=.99 survey 2). A composite score of the socioeconomic
status of each job was derived by computing the mean value assigned by all three raters.
Some of the commonly reported careers had socioeconomic indices that were rated as
follows: Athletes — 48.90, doctor - 88.28, engineer — 76.41 , lawyer — 88.42, nurse — 46.40,
police officer — 38.01, teacher - 52.99, veterinarian — 86.60. See Appendices D (Time 1)
and E (Time 2) for a list occupational titles mentioned by the children in this study and
their coded prestige scores for desired careers and expected careers for the first survey and

the follow-up survey one year later.

Child Human Capital Predictors
Self-competence

The Child Self-Perception profile (Harter, 1982) provides a multidimensional approach
to measuring constructs that are sources of self-esteem for children (See Appendix A). Six
dimensions of this profile were included in this study and these include scholastic
competence, social competence, athletic competence, physical appearance, behavioral
conduct, and self-worth. A five-item scale, with a reliability of 0.71 , was selected using the
first factor revealed in the exploratory factor analysis. Such an analysis of this scale was
necessary after confirmatory factor analyses of the original scales revealed that the original
factors were inappropriate for this sample. The final scale developed for use in this study
included 3 items originally intended to measure behavioral conduct, and one item each
from the general self-worth and scholastic self-competence dimensions. The items selected
for the final and most reliable measrn'e of child self-worth in this study included the
following questions:

0 Don't do things shouldn't

0 Happy with how they do things

0 Behave well

0 Don’t get in trouble

0 Easy to figure answers

Several steps were taken in the development of this final measure. A confirmatory
factor analysis of the original six dimensions (See Appendix F) revealed less than
satisfactory reliabilities, ranger from 0.37 to 0.46. Nearly all question items loaded more

highly on factors other than the one it was intended to measure. The average correlation of

95

question items within these designated factors only ranged from 0.09 to 0.18. Pungello,
Moore, & Campbell (2000) reported similar findings. The researchers found that the factor
structure of Harter’s self-perception profile for children, which had been originally normed
on white middle- and upper-class families, was not appropriate for their study which
consisted primarily of African-American families drawn from an economically
disadvantaged sample. The present study also focused on economically disadvantaged
families and had a more ethnically diverse sample than the ones originally used to develop
Harter’s child self-perception profile, so an exploratory factor analysis was necessary. An
exploratory factor analysis (See Appendix G) of the questions in the child-perception
profile revealed twelve factors instead of six. The reliabilities of these new factors were
greatly improved over the reliabilities for the original factors. The items in the first factor,
with reliability of 0.71 , were selected as a measure of child self-competence for this study.

The format of the child self-perception profile was also revised for use in this study.
The instrument was been designed as a self-administered paper and pencil survey, so the
questions had to be modified for use over the telephone. For each survey question children
were read statements about two different types of children. They were then asked if they
were more like the first kid or the second kid. After they answered which kid they were
most like, then they were asked if that was really true for them or only sort of true for them.
These statements were used to compute a 4-point Likert scale for each question group.
Appendix A contains the full set of questions. Sample items fi'om each of the original
dimensions of the survey follow:

(Q1) scholastic competence - Some kids feel that they are very good at

their school work. Other kids worry about whether they can do the school

work assigned to them. (Q2) social competence - Some kids find it hard to

make friends. Other kids find it's pretty easy to make fiiends. (Q3) athletic

competence - Some kids do very well at all kinds of sports. Other kids don't

feel that they are very good when it comes to sports. (Q4) physical

appearance - Some kids are happy with the way they look. Other kids are

not happy with the way they look. (Q5) behavioral conduct - Some kids

often do not like the way they behave or act. Other kids usually like the way

they behave or act. (Q6) self-worth - Some kids are often unhappy with

themselves. Other kids are pretty happy with themselves.

Academic Achievement

To measure academic achievement, an average of children’s most recent grades for
math, science, social studies, and language arts/English were included using both mother
and child reports of children’s grades. Mother’s reports of children’s grades were included
because of concerns about the reliability of children’s self-reports. Children’s self-report of
grades were still included because of their potential importance as an indicator of children’s
perceived academic abilities regardless of their achievement reported by mothers. Over a
dozen possible grading schemes were reported. All grades were converted into a 5-point
Likert scale with 5 being the highest grade to be obtained (e.g., A, /+, outstanding, etc.).
The relationship between mother and child reports of children’s grades has not been

widely researched since most educational studies rely on actual student grades reported by
the schools. As Table 15 demonstrates, children in this study tended to report higher
grades than mothers in most subject areas. None of these differences were significant,

although the difference in reports for math grades approaches significance. The

97

correlations between mother and child reports of grades were significant. As a general
measure of academic achievement, the internal consistency of grades among these four
classes were much higher for mother’s reports than for child reports of grades. The internal
consistency reliability analysis for the four grades reported by mothers was 0.82 but only
0.66 for children’s reports of their grades.

Mother Human Capital Predictors

 

Self-Competence
Similar to the children, the self-competence of mothers was measured using
selected items from the Self-Perception Profile for adults (Harter, 1985) which measured
several constructs related to sources of adult self-esteem. Three dimensions used in this
survey included global self-worth, job competence, and adequacy as a provider (See
Appendix B for a list of all questions). The confirmatory factor analysis revealed
reliabilities of 0.44 to 0.56 for these factors (See Appendix H). Given these low reliabilities
and concerns about the inappropriateness of these measures for non-white, economically
disadvantaged samples (Pungello, Moore & Campbell, 2000), an exploratory factor
analysis was conducted (See Appendix I). This analysis revealed improved reliabilities
with four factors instead of three factors. The most reliable factor was the second factor
with 4 items from the provider adequacy scale with reliability of 0.61. These questions
were included in the final scale designed to measure mother’s perception of these:
0 Competence in adequately providing for the material necessities of life
0 Competence in providing adequate support for themselves and others
- Competence in providing adequately for the needs of those who are important

0 Satisfaction with how they provide for the important persons in their lives

98

Table 15 Matched Pairs Comparisons

 

 

 

Descriptive Statistics Correlations Test of
Differences
GRADES Mean N SD SEM r p t df p
Pair] MATH—mother report 3.8] 159 1.07 0.08 0.44 0.00 -l.90 158 0.06
MATH- child report 3.97 159 0.88 0.07
Pair2 SCIENCE-motherreport 3.70 159 0.96 0.08 0.51 0.00 -0.69 158 0.49
SCIENCE- child report 3.75 159 0.91 0.07

 

Pair3 LANGUAGE ARTS-motherreport 3.84 159 0.97 0.08 0.47 0.00 0.16 158 0.87

LANGUAGE ARTS- child report 3.83 159 0.89 0.07

 

Pair4 SOCIAL STUDIES-motherreport 3.64 159 0.98 0.08 0.45 0.00 -l.44 158 0.15

SOCIAL STUDIES- child report 3.75 159 0.90 0.07

 

PairS GPAbasedonmotherreports 3.75 159 0.81 0.06 0.60 0.00 -l.49 158 0.14

GPA based on child reports 3.83 159 0.67 0.05

 

The format of the instrument was similar to the child profile, so the same protocol
was used in converting the paper and pencil survey to an interview format. Mothers were
read statements about two types of adults and were asked which person they were most
like. Then they were asked if this was really true or only sort of true for them. Question
groups were recoded into 4-point Likert scales. Sample questions from each of the original
factors are described below:

(Q1) Job Competence - Some adults are not satisfied with the way they do

their work but other adults are satisfied with they way they do their work.

(Q2) Provider Adequacy - Some adults are satisfied with how they provide

for the important people in their lives but other adults are dissatisfied with

how they provide for these people. (Q3) Global Self-worth - Some adults

question whether they are a worthwhile person but other adults are quite

pleased with themselves.

Academic Achievement

The educational background of mothers was assessed by asking mothers to report the
highest grade level obtained at the time of the first survey. Grade levels were coded to
measure the number of years of education completed (e. g., “less than 9'“ grade = 9 years of
education, “High school” = 12 years of education). No additional verification data was
available to assess the reliability of this information.

Socioeconomic status of most recent job

The socioeconomic status of the mothers' current or most recent job was coded using
the same socioeconomic index (Stevens & Cho, 1985) that was used to code the children's

careers. Three trained advanced graduate students coded the corresponding socioeconomic

100

value of the mother’s most recent jobs. The inter-rater reliability correlation of these codes
was r=.93 for the first survey. See Appendix E for a list of jobs reported by mothers and
the codes assigned to them.

CommunilCapital Predictors

Zip codes were used to compute indicators of commrmity capital to predict human
capital resources of the mother that could indirectly influence child career aspirations.
Clients in the study sample resided in 27 different zip codes fiom the 42 zip codes
represented in the random sample. Measurement of community opportunity structures are
still largely undeveloped (Furlong & Cartrnel, 1994), so the zip code level census data
provides a useful information for this community level of analysis. Zip code boundaries
have served as a proxy variable for community boundaries (Carter, Huber-Yoder, LaMore,
Lerner, Lichty, Rosenbaurn, 1997). This level of data provides information about the
mother and child’s most proximal community, and it is the one that they are most
embedded within. One of the assumptions of this measurement is that the mother and child
remained in the same zip code, or a nearby zip code with similar characteristics, if they
changed addresses during the study time period. This assumption will be tested by
assessing the constancy of mothers’ addresses during the study.

Socioeconomic Status of community jobs

The status of j obs represented in the community (zip code area) was measured
using occupation codes from the 1990 Census (U .8. Census Bureau, 1990, STF3B P78). A
socioeconomic status index score was derived for each zip code. This was computed by
assigning socioeconomic ratings to each of the broad occupational classifications (e.g.,

managerial, technical, service) using an index revised by Stevens & Cho (1985). The codes

101

were weighted by the number residents in each occupational category. The mean
socioeconomic status of these occupations was computed for each client’s zip code.

Educational Achievement

The level of education represented in the community (zip code area) was measured
using educational attainment data from the 1990 Census (U .8. Census Bureau, 1990,
STF3B P60). An educational attainment score was derived for each zip code. This was
computed by finding the median years of education completed by residents. The Census
education categories were recoded into numerical values (e. g., “less than 9th grade = 9 years
of education, “Bachelor’s degree” = 16 years of education). These numerical values were
weighted by the number of residents in each category for the purpose of computing the
mean years of education attained by individuals in the community.

Child Demographics

 

The age of children was measured using child self-reports of age and grade level.
No reliabilities were available for this information. The gender of children was reported by
mothers. Due to errors in the data collection process, children were not asked to report
their race or ethnicity. As a proxy for this variable, the self-reported ethnicity of mothers
was used to approximate the ethnicity of their children. This presents some obvious
limitations due to potential differences in mother-child racial characteristics and racial
identity associated with adoption, interracial parental compositions and multiple ethnic

heritages.

102

 

Chapter 5 Results
This chapter will review three sets of analyses. The first analysis presents the results
of the hypotheses from the final structural equation model testing an ecological model of
career aspirations. The second set of analyses examines hypotheses related to whether or
not child demographic characteristics influenced career aspirations. The third analysis
provides post-hoe examination of how often mothers’ reported changes in their zip codes of

residence during the period of the study, the stability of children’s’ career aspirations over

-- Amrnfi
.

time, and similarity between expected and desired careers.

Before proceeding with the results of these analyses, the correlation matrix and

 

descriptive statistics of study variables will be discussed (See Table 16). The average age
of children in this study was 11 years old. The average number of years of education held
by the community members of mothers and children in this study was just under 13 years.
The average socioeconomic status of jobs held by these community members was just over
38, while mother’s average jobs SES status was slightly lower at 24. This is considerably
lower than the SES of the jobs desired or expected by children at time 1 or 2 of this study.
Their average SES jobs scores ranged from 54 to 62. On a scale from 1 (E or F) to 4 (A),
children’s average grades were in the upper “B” range as values reported by both mothers
and children were 3.75 or higher. On a scale of 1 to 4, with 4 being high self-competence,
both mothers and children had average self-competence scores in the upper range.
Children’s self-competence averaged closed to 3 while mothers’ average self-competence

scores were over 2.5.

103

Table 16 Correlation Matrix and Descriptive Statistics

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Descriptive Statistics Correlations
4 Mean SD n Rel. 1 2 3 4 5 6
1 MOTHER RACE 1.57 0.50 157 1.00 r 1
l=white 9 N/A
2=non-white g 157
2 CHTLD SEX 1.48 0.50 1 1 I 1.00 r -0.05 1.00
1=fernale p 0.60 N/A
2=ma1e g 110 11 1
3 CH—ILD AGE 10.99 1.54 159 1.00 r -0.11 0.18 1.00
p 0.19 0.07 N/A
r_r 157 11 1 159
4 COMMUNITY 12.80 0.66 159 1.00 r -0. 12 0.13 —0. 12 1.00
EDUCATION LEVEL 9 0.14 0.17 0.13 N/A
3 157 111 159 159
5 COMMUNITY JOB 38.12 3.24 159 1.00 r -0.04 0.14 -0.09 0.91 1.00
SOCIOECONOMIC Q 0.65 0.14 0.25 0.00 N/A
INDEX 9 157 111 159 159 159
6 MOTHER EDUCATION 12.41 1.88 159 1.00 r -0.14 -0.08 -0.02 0.17 0.20 1.00
LEVEL 9 0.09 0.38 0.81 0.03 0.01 N/A
9 157 111 159 159 159 159
7 MOTH—ER SELF- 2.53 0.83 159 0.60 r 0.04 0.08 0.09 -0.05 -0.01 -0.04
COMPETENCE p 0.62 0.39 0.25 0.50 0.87 0.62
_ n 157 111 159 159 159 159
8 MOTHER JOB 24.13 7.65 159 0.93 r -0.02 0.00 0.07 0.08 0.10 0.37
SOCIOECONOMIC p 0.77 0.96 0.36 0.30 0.22 0.00
INDEX 9 157 111 159 159 159 159
9 CHILD GRADES 3.75 0.81 159 0.82 r 0.06 -0.40 -0.12 -0.08 -0.05 0.17
REPORTED BY 9 0.43 0.00 0.14 0.29 0.55 0.03
MOTHER g 157 111 159 159 159 159
10 CHTD GRADES 3.83 0.67 159 0.66 r 0.01 —0.26 -0.19 -0.10 -0.06 0.17
REPORTED BY CHILD p 0.86 0.01 0.02 0.20 0.43 0.03
_ g 157 111 159 159 159 159
11 CHILD SELF- 2.94 0.75 159 0.72 r 0.11 -0.07 -0.11 -0. 10 -0.02 0.10
COMPENTENCE p 0.15 0.44 0.17 0.23 0.78 0.20
g 157 111 159 159 159 159
12 CHTLD DESIRED JOB T1 60.27 17.51 159 0.98 r -0.02 -0.03 0.13 -0. 14 -0.08 0.09
2 0.76 0.76 0.1 1 0.08 0.32 0.25
n 157 111 159 159 159 159
13 CHILD EXPECTED JOB 53.92 17.23 159 0.97 r -0.02 0.03 0.00 -0.09 -0.06 0.13
T1 2 0.80 0.77 0.99 0.28 0.44 0.10
n 157 111 159 159 159 159
14 CHILD DESIRED JOB T2 58.49 23.58 89 0.99 r 0.16 -0.19 -0.22 0.10 0.14 0.26
p 0.13 0.07 0.04 0.35 0.19 0.01
g 88 89 89 89 89 89
15 CHILD EXPECTED JOB 61.82 25.04 78 0.99 r 0.26 -0.23 -0.15 -0.1 l -0.02 0.19
T2 9 0.02 0.05 0.20 0.36 0.89 0.10
g 77 78 78 78 78 78

 

104

Table 16 (Continued)

 

Correlations (continued)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

7 8 9 10 11 12 13 14 15
1 MOTHER RACE
l=white
2=non-white
2 CHILD sex
1=female
2=male
3 CHILD AGE
4 COMMUNITY EDUCATION LEVEL r
I
5 COMMtUNITY JOB SOCIOECONOMICINDEX ‘
6 MOTHER EDUCATION LEVEL
—7 —MOTHER SELF-C—OMP‘ETEN'CE 1.00 --
MA I.
159
8 MOTHER JOB SOCIOECONOMIC [ 0.02 1.00
INDEX 9 0.79 N/A
9 159 159
9' —CHILD —GRAD' E's—RE—Po‘RTED BY [ 0.05 0.05 1.00
MOTHER p 0.53 0.54 N/A
_ 13 159 159 159
10 CHILDGRADES REPORTED BY r -0.05 -0.01 0.60 1.00
CHILD p 0.51 0.88 0.00 N/A
r_1 159 159 159 159
11 CHILD SELF-COHERENCE r 0.05 0.09 0.28 0.26 1.00
g 0.53 0.25 0.00 0.00 N/A
9 159 159 159 159 159
12 CHILD DESIREDJOB T1 r 0.08 0.27 0.15 0.19 0.17 1.00
p 0.34 0.00 0.06 0.02 0.03 N/A
[1 159 159 159 159 159 159
13 Cl-IILDEXPEC'I'EDJOBTI [ 0.01 0.15 0.19 0.19 0.11 0.66 1.00
p 0.94 0.06 0.02 0.02 0.17 0.00 N/A
[1 159 159 159 159 159 159 159
14 CHILD DESIREDJOB'I‘Z [ -0.06 0.32 0.31 0.25 0.26 0.39 0.34 1.00
p 0.57 0.00 0.00 0.02 0.01 0.00 0.00 N/A
3 89 89 89 89 89 89 89 89
15 CHILD EXITEC'I'EDJOBTZ [ 0.06 0.15 0.44 0.25 0.32 0.36 0.29 0.61 1.00
p 0.59 0.20 0.00 0.03 0.00 0.00 0.01 0.00 N/A
Q 78 78 78 78 78 78 78 78 78

 

105

Proposed Structural Equation Model

The model below shows the hypothesized relationships among community, mother,
and child capital predictors using an ecological approach. In general, community capital
was hypothesized to predict mother capital, which would in turn predict child capital,
which would predict child capital and career aspirations. Community capital consisted of
the average socioeconomic status of jobs held by people in the community of the mothers’
residence, as well as the average level of education obtained by people in that same
community. Mother capital included the socioeconomic status of past or present jobs,
educational attainment level, and self-competence for work and life tasks. Child capital
included academic achievement and self-competence related to a variety of self-
perceptions. This model reflected a hypothesized flow of educational, job, and
psychological resources from community, to mother, and to the child.
Final Structural Equation Model

The initially proposed model was tested using a structural equation approach.
Confidence intervals were examined to determine which paths should be eliminated fi'om
the model. Modification indices were also examined to identify which paths could
contribute to the model through their addition. This iterative process was continued until
confidence intervals and modification indices indicated that the significant paths were
included. The results of these steps are presented in the final structural equation model in

Figure 5 and the expected ranges for these path coefficients are presented in Table 17.

106

 

 

Community
education level

 

 

0. 91

 

 

 

SES of
Community

 

 

0.17

 

 

Child self-
competence

 

 

T 0.18

 

 

 

Mother
education level

0.19

 

 

Child grades
rated by mother

 

 

 

0. 38

 

v

I0. 82

 

 

Child grades
rated by child

 

 

0. 24

 

 

 

SES of mother’s
job

0. 29

 

 

SES of child’s
desired job

 

 

 

107

I 0.68

 

 

SES of child’s
expected job

 

 

Figure 4 Predicted Model of Children's Career Aspirations

 

 

 

Community
Education Level

 

 

 

 

Mother
Education Level

 

 

 

 

Mother Self-
Competence

 

 

 

 

Community Job
SES

 

 

 

 

Mother Job SES

 

 

Figure 5 Final Structural Equation Model

108

 

 

Child Grades
rated by Mother

 

 

 

\.

1

Child Grades
rated by Child

 

 

 

 

 

Child Self-
Competence

 

 

 

 

 

SES of Child’s
Desired Job

I'd-

 

 

 

 

t

 

 

l

SES of Child’s
Expected Job

 

 

 

 

Table 17 Final Path Model (Standardized) Coefficients

 

 

 

 

 

 

 

 

 

 

 

95% Confidence
Intervals

Direct paths included in the final model Path Standard Lower Upper

Coefficient Error Bound Bound
Community education level 9 Mother education level 0.17 0.08 0.01 0.33
Mother education level 9 Child grades rated by mother 0.38 0.09 0.24 0.52
Child grades rated by mother 9 Child grades rated by 0.82 0.07 0.68 0.96
child
Child grades rated by mother 9 Child self-competence 0.18 0.09 0.00 0.36
Mother education level 9 SES of mother’s job 0.38 0.07 0.24 0.52
SES of mother’s job 9 SES of child’s desired job 0.29 0.08 0.13 0.45
Community educaton level 9 SES of community jobs 0.91 0.01 0.89 0.93
SES of child’s desired job 9 SES of child’s expected job 0.68 0.05 0.58 0.78
Child grades rated by child 9 SES of child’s desired job 0.24 0.10 0.04 0.44

 

109

Goodness of Fit and Power of the Final Structural Equation Model

The goodness of fit indices highlight the appropriateness of the final model. The
overall chi square analysis fi'om Hunter Path analysis was non-significant (X2= 14.83,
df=35, p=0.999) suggesting that the model did not significantly differ fiom the data. Two
other indices from AMOS analysis indicated that the model was better than a baseline
model (Arbuckle, 1977). The goodness of fit index (GFI, JOreskog & SOrbom, 1984) was
0.960 which suggested that the specified model was better than an independent model with
no specified paths since this value is close to 1.0 on a scale of 0 to 1.0. Similar to the GFI,
the normed fit index (N FI, Bentler & Bonett, 1980), which was 0.940, suggested that the
specified model was better than an independent model since this value was close to 1.0.
Lastly, the root mean square error of approximation (RMSEA, Browne & Cudeck, 1993)
showed a reasonable approximation of errors in the population since the resulting RMSEA
value of 0. 000 was less than 0.05 which has been considered to be a close fitting model
(Browne & Cudeck, 1993). Furthermore, the 95% confidence intervals for the RMSEA
ranged fiom 0.000 to 0.048, which indicated that the not-close-fit model could be rejected,
since the entire confidence interval for the RMSEA was less than 0.05 (Browne & Cudeck,
1993)

Given the difficulty of assessing power in individual path models, the power of the
final model was examined using the analysis provided by MacCallum, Browne, &
Sugawara (1996) shown in Table 18. Their analysis allows researchers to estimate power
based on the root mean square error of approximation index of fit (RMSEA), degrees of
freedom, and alpha levels. In the final model presented in this paper, the RMSEA showed

that the final model could be considered a close fit. Power analyses for models with a close

110

fit are presented in the middle column of Table 19. The final model also had 35 degrees of
freedom which is in between the degrees of freedom (30 and 40) available in Table 18.

The sample size in the final model was 159 which is slightly over halfway between the
sample sizes (100 and 200) available in Table 18. Using an 0.05 alpha level, one can
ascertain that the power of this final model would be greater than 0.30 but less than 0.69

based in the data presented in Table 18.

Table I8 Power estimates by fit and sample size (MacCallum Browne, & Sugawara,
1996)

 

Level of model fit based on RMSEA

 

 

 

df Sample size Exact fit Close fit Not close fit
30 100 0.237 0.307 0.187

200 0.512 0.585 0.424
40 100 0.279 0.368 0.224

200 0.606 0.688 0.523

 

Community capital influences on mother capital

 

Community capital resources were hypothesized to predict similar resources of the
mother. Although community capital did directly or indirectly predict mother resources it
was not in the manner predicted. The results of these hypotheses are described below

further:

 

7 Power estimates are based on alpha level of .05 and taken fi‘om MacCallum, Browne, & Sugawara,
1996, p. 142.

111

1. The average level of the educational attainment of the mother ’s community
will positively predict mother ’s educational attainment level.

This hypothesis was supported as there was a moderate relationship (8 = 0.17)
between the years of education attained by community members and the years of education
attained by mothers in this study.

2. The average socioeconomic status of jobs held by residents of the mother ’s
community level of the educational attainment of the mother’s community will positively
predict the socioeconomic status of the mother’s current or most recent job.

This hypothesis was not supported since the socioeconomic status (SES) of jobs
held by community members did not directly predict the socioeconomic status of mother’s
jobs directly. However, community capital in the form of community education levels
indirectly predicted the SES of mother’s jobs through the education level of mother’s own
attainment. The SES of community jobs directly predicted mothers’ educational level,

although the relationship was small (0 = 0.06, which was equal to 0.17 * 0.388).

Mother capital influences on children

Mother capital resources were hypothesized to directly predict similar resources of
their children in terms of job, education, and psychological resources. Both the job
resources and educational resources of mothers and children were directly related.

However, children’s self-competence was indirectly predicted by mother’s educational

 

' This weight of this path was calculated by multiplying the weights of the two paths from
community education level to mother education level to SES of mother’s job

112

resources rather than directly by mother’s self—competence. The results of these hypotheses
are described in more detail:

3. Mother 's level of self-competence will positively predict children ’s level of
self-competence.

This hypothesis was not supported. Mothers’ level of self-competence was not
significantly directly related to child self-competence. However, children’s self-
competence was predicted directly by their grades as reported by their mothers and this
relationship was moderate (Q = 0.18). Mother’s self-competence was not found to predict
other variables within the model and was dropped from the final model as it did not appear
to beindirectly related to any child outcomes.

4. Mother’s level of educational attainment will positively predict child ’3
academic achievement.

This hypothesis was supported as the educational attainment of mothers was
positively related to children’s grades. Mother educational attainment was moderately and
directly related to children’s grades as reported by their mothers (5 = 0.19). Mother’s
educational attainment was also moderately related to children’s grades reported by the

children ([3 = 0.15, equal to 0.19 * 0.82). However, this was indirectly related through the

strong (0 = 0.82) relationship between child’s grades reported by mothers and children.
5. The socioeconomic status of the mother’s current or most recent job will
positively predict the socioeconomic status of children ’s career aspirations.
This hypothesis was supported. The socioeconomic status (SES) of mothers’ job
levels directly predicted the SES of the jobs children desired to have and indirectly

predicted the SES of the jobs children expected to have. The SES of mothers’ jobs had a

113

strong relationship to the SES of children’s desired jobs ([3 = 0.29) and a moderate
relationship to children’s expected jobs (0 = 0.20, equal to 0.29 * 0.68) through the strong

relationship between children’s desired and expected jobs ([3 = 0.68)

Children’s resources influencing career aspirations

 

Children’s internal resources of academic achievement (grades) and psychological
self-competence were hypothesized to directly influence the types of careers they desired
and expected. These hypotheses were primarily supported and described in more detail
below:

6. Children ’s desired jobs will predicted their expected jobs.

The careers desired and expected by children were positively related to one another
([3 = .68) and this relationship was strong.

7. Children’s self-competence levels will positively predict the socioeconomic
status of their desired and expected career aspirations.

This hypothesis was not supported. Children’s ratings of their self-competence was
not found to predict the socioeconomic status of the careers children expected or desired to
have.

8. Children ’s reports and mother 's reports of children ’s grades will be similar.

This hypothesis was supported. Mothers and children’s reports of children’s grades
were positively related to one another (0 = 0.82). Table 19 shows the direction of bias in
the reports of grades between mothers and children. For all subject grades, except language

arts, children tended to report higher grades for themselves than their mothers and the

114

Table 19 Matched Pairs Tests of Differences of Mother's and Children's Reports of Grades

 

 

 

 

 

 

 

Tests of Differences Correlations
Paired Samples Mean SD N Mean SD t p r p
Math grades — mom 3.81 1.07 159 -0.16 1.04 -l.90 0.06 0.44 0.00
Math grades - child 3.97 0.88
Science grades - morn 3.70 0.96 159 -0.05 0.92 -0.69 0.49 0.51 0.00
Science grades - child 3.75 0.9]
Language arts grades - mom 3.84 0.97 159 0.01 0.96 0.16 0.87 0.47 0.00
Language arts grades — child 3.83 0.89
Social studies grades — morn 3.64 0.98 159 -0.11 0.99 -1.44 0.15 0.45 0.00
Social studies grades — child 3.7 5 0.90
Overall GPA - mom 3.75 0.81 159 -0.08 0.67 -1.49 0.14 0.60 0.00
Overall GPA — child 3.83 0.67

 

115

differences were significant. Mothers tended to report slightly higher grades than their
children did on language arts grades.

9. Children '5 academic achievement scores (rated by both mother and child)
will positively predict the socioeconomic status of their desired and career aspirations.

Children’s grade point averages predicted career aspirations but the relationship
depended on whether the grades were reported by mothers or children. Children’s self-
reported grades were directly and strongly related to the SES of the jobs children desired to
achieve (1} = .19) but not the careers they expected to have. 0.24) and indirectly and
moderately related to the expected jobs ([3 = 0.16, equal to 0.24 * 0.68). Mother’s reports
of children’s grades were also to the SES of the desired ([3 = 0.20, which equals 0.82 *
0.24) and expected (0 = 0.13, equal to 0.82 * 0.24 * 0.68) careers of children, and these
relationships were indirect through children’s reports of grades. 9b. What additional paths
were added to the model that were not originally hypothesized?

To create the best fitting model two additional paths were required that linked
forms of capital within communities and mothers. Community education level and SES of
community jobs were found to be strongly related (0 = 0.91). Mother educational levels
and the SES of mother’s jobs were strongly related (0 = 0.3 8) as well.

9c. What are the overall pathways predicting children 's career aspirations?

In making an assessment of which pathways predict Career aspirations it is
necessary to consider the direct as well as the indirect pathways leading to this outcome.

As noted earlier, the path coefficient of the indirect pathways is equivalent to the product of

116

coefficients of the direct paths”. As Table 20 indicates, there were multiple pathways that
ultimately predicted children’s career aspirations. Children’s own capital was found to
directly relate to career aspirations through grades (path = 0.24) and indirectly through self-
worth via school grades (path = 0.04). Mother’s capital was found to directly relate to
career aspirations through job SES (path = 0.29) and indirectly through educational
attainment via job SES (path = 0.04). Community capital, measured by education level
and job SES, was indirectly related to children’s career aspirations through two different
pathways. One was through the educational level of mothers, (0.01) while the other
pathway was through the job SES level of mothers (0.02).

10. Do the socioeconomic status of children ’s career aspirations significantly
vary between black and white children?

No significant differences were found between desired jobs and expected jobs
except among children of black mothers (See Table 21). Children of black mothers
expected to achieve higher status careers than they desire E(1,87) = 4.19 p = 0.04]. There
were no significant differences on desired job aspirations based on race, but there were
significant differences in expected jobs. Children of black mothers expected to achieve
higher socioeconomic status careers than children of white mothers (Mean difference =

13.63, Standard error=5.21, p=0.03).

 

9 Directions of arrows are irrelevant in this analysis.

117

1 1. Do the socioeconomic status of children ’s career aspirations significantly
vary by grade levels?
No significant differences on either desired or expected career aspirations were found based
on grade level (See Table 21). This suggests that the career aspirations were stable over
time in regard to the socioeconomic quality of the jobs.

12. Do the socioeconomic status of children ’s career aspirations significantly
vary by age groups?

No significant differences on either desired or expected career aspirations were
found based on age. This suggests that the career aspirations were stable over time in

regard to the socioeconomic quality of the jobs.

118

Table 20 Overview of Pathways Predicting Child's Desired Jobs by Ecological Level

 

 

 

 

 

Pathway Path Type Path
Coefficient

Child Pathways

Child's grades to child's desired job direct 0.24

Child's self-worth to child's desired job indirect 0.04

Mother's Pathways

Mother’s job SES to child's desired job direct 0.29

Mother's education level to child's desired job indirect 0.04

Community Pathways

 

Community education level to child's desired job
via mother's job SES indirect 0.02
via mother's educational level indirect 0.01
Community job SES to child's desired job
via community education level and mother's job SES indirect 0.02
via corrrmunity education level and mother’s indirect 0.01

educational level

 

119

Table 21 Career Aspirations by Child Demographic Characteristics

 

 

 

 

 

 

 

 

 

 

Desired Job
M SD N

Females 63.19 22.81 55

Males 52.73 22.05 47
Difference t(100) = 2.34 p_= 0.02, g = .23
Tyears old 81.43 na 1

8 years old 55.32 23.39 4

9 years old 63.21 24.30 18

10 years old 60.08 22.39 20

11 years old 58.61 22.70 19

12 years old 55.52 22.94 26

13 years old 53.90 25.11 14
Difference If (6,95) = 0.47 p = 0.83, g = .17
Grade 2 81.43 na 1

Grade 3 64.77 26.11 9

Grade 4 26.1 1 21.33 20

Grade 5 55.86 23.73 26

Grade 6 56.22 21.06 23

Grade 7 57.90 27.39 18

Grade 8 59.65 20.27 5
Difference E(6,95) = 0.38 p = 0.89, e_te = .15
13ka 59.18 21.46 47

White 54.10 24.00 42

Arab 67.10 18.91 8
Difference E(2,94) = 1.35 p = 0.27, eLa = .17

 

 

 

Expected Job
M SD N
66.87 23.01 48
53.99 24.35 43

t(89) = 2.59 p_= 0.01, et_a = .26

 

 

26.05 na 1

63.66 30.28 4

64.35 24.75 17
62.28 20.46 19
59.14 28.10 17
65.90 22.41 21
48.70 25.1 1 12

E (6,84) = 1.08 p = 0.38, g = .27

 

 

26.05 na 1
67.39 27.05 8
66.65 24.08 20
51 .3 1 22.67 23
61.47 24.61 22
65.82 25.00 13
61 .32 20.27 4

§(6,84) = 1.33 p = 0.25, g = .30

 

 

68.70 *22. l 3 42
55.07 ‘24.60 38
57.93 22.34 8

E(2,85) = 3.55 p = 0.03, ete = .28

 

‘difference between groups is significant at .05 level

120

Post-hoe analysis of maternal employment on child aspirations

A correlation analysis was conducted to determine whether maternal employment
factors at time 1 impacted child career aspirations at time 2. The number of hours that
mothers reported working in the first survey were not significantly related to either
children’s desired career aspirations Q = -.086, p = .388) or their expected careers (r = -
.025, p = .811). Mother’s work status (l=not presently working, 2=presently working) was
also not significantly related to either children’s desired (1' = -.046 p = .646) or expected

careers (g= .048 p = .649).

Post-Hoe Comparisons of Career Aspirations Over Time

 

Additional analyses were conducted to assess the stability of desired and expected
career aspirations over time. Strong intercorrelations were found among the career
aspirations over time (See Table 22). Matched pairs t-tests indicated that the SES of
children’s desired careers were significantly higher than the SES of their expected careers
at time 1 Lt(5.59,158, p=0.00)] although there were no significant differences at time 2 [1(-
0.60,77, p=0.54)]. There were no significant differences in the SES of children’s desired
careers fiom time 1 to time 2 Lt(0.42,88, $0.68)], but children’s expected careers

significantly increased over time [t(-2.81,77, p=0.006)]

121

Table 22 Pairwise Correlation Matrix of Desired and Expected Career Aspirations Over
Time

 

Correlations
Mean SD Desired] Desired 2 Expected] Expected]
Desired Career 60.27 17.51 1.00

 

 

Time 1 (n=159)

Desired Career 58.49 23.58 0.39“ 1.00

Time 2 (n=89) (n=89)

Expected Career 53.92 17.23 0.66" 0.34" 1.00

Time 1 (n=159) (n=89) (n=159)

Expected Career 61.82 25.04 0.36“ 0.61" .29" 1.00
Time 2 (n=78) (n=78) (n=78) (n=78)

 

"”" significant at p<.01 two tailed

Post-Hoe Assessment of the Permanency of Mother’s Residence

 

Archival data from the MIFIA was analyzed to determine whether or not mothers
reported changes in their zip code of residence during the study period. Figure 6 shows that
the range of clients moving each month varied from 0% to less than 5% each month. The
median and modal number of moves during the period of the study was zero. The median
average number of moves during the study was 0.28 people per month. The number of
times clients moved during the entire study is shown in Table 23, which indicates that over
seventy-nine percent of the survey respondents remained in the same zip code for the 24-
month period of the study. This denotes that there was a 21% probability that sometime
during the study clients would reside in a community other than the one used to compute

their community capital predictors.

122

Table 23 Overview of Survey Respondents (Mothers) Residential Mobility

 

 

Number of moves Ntunber of Mothers Percent of Mothers Cumulative %
during the study
0 169 79.3% 79.3%
1 36 16.9% 96.2%
2 3 1.4% 97.7%
3 3 1.4% 99.1%
4 2 0.9% 100%
Total 213 100%
Percent of mothers moving slnce last month
4.50%
4.00% r
3.50% lAk
3.00% 3
/A\ /\ J! \\ A
o I L
2.00 /0
V \l \/
1.00% x
0.50%
0.00%

 

 

 

 

 

 

 

 

 

 

 

12 345678910111213'1415161718192021

Month number

Figure 6 Percent of Clients Changing Addresses from the Previous Month (by Month)

123

 

Summa_ry

Overall, the predicted ecological model was supported. Community educational
attainment predicted mother’s educational attainment, which in turn predicted academic
achievement and self-competence of children. Children’s grades and the SES of mother’s
jobs predicted children’s desired and expected jobs. The SES of their desired and expected
careers were similar to each other and over time, and no differences were found by age.
However, females had higher desired and expected careers than males, and children of
White mothers had higher career expectations than children of Black mothers. Although
this model does not explain how much socialization or access to opportunities explain the.
impact of community, mother, and child capital on children’s career decisions, it does
indicate that each is important in the broad picture of human capital. Results suggest that an

ecological approach is needed to improve the career outcomes for children living in

poverty.

124

Chapter 6 Discussion
Career aspirations of children have been linked to their future economic
achievements, although children living in poverty have often been excluded from such
research. The present analysis identified factors predicting career aspirations for children
living in poverty. Such factors could potentially affect the economic future of this
economically vulnerable population, assuming that the relationship between aspirations and Ir
achievements is the same for children living in poverty as it is for middle and upper class

children. Results of this study revealed that an ecological perspective was useful for

 

understanding the career progression of these children. It also revealed that there were

“many-1..“ k .17-: .

some unique aspects to the career development of these children that were different for
non-poverty populations. A discussion of these findings, implications, and limitations are

outlined below.

Comparing Career Aspirations of Study Children to Existing Literature

 

This study was also initiated to better understand the career aspirations of children
who have often been excluded from research because they are both younger and are living
in poverty. This study examined the career aspirations of children much younger than
usually interviewed. The majority of studies reviewed in this paper were conducted with
students aged 13 and older, but this analysis focused on 9 to 13 year-old children. These
studies also examined the career aspirations for children living in economic disadvantage
and were rarely included in the studies available for this review. Given that these children

will need to increase their earning potential beyond that of their farrrily in order to achieve

125

economic independence, it was deemed critical to understand predictors of the SES of
careers desired and expected by children.

Previous meta-analytic reviews (See Table 13 earlier) of students from primarily
non—economically disadvantaged communities highlighted the expected effect sizes of
individual variables on children’s career aspirations. To make accurate comparisons, these
effect sizes were compared to the univariate correlations reported in Table 16. An
examination of the univariate correlations in this study revealed many similarities to studies
of other children.

The previous reviews of studies also suggested that there were no consistent age,
race, or gender influences on career aspirations. Similar to these studies, there were no age
effects detected for children in this study, and career aspirations appeared to be stable over
time as expected. Although this is a cross-sectional sample, this offers some indication that
career aspirations may be stable with age similar to findings of Odom, Woods, &
McClellan, (1995). However, females were found to have significantly higher career
aspiration than males and White students had higher career expectations than Black
students although they did not differ in the careers they desired.

Similar to studies of other children, this study found that child grades, child self-
competence, parent education, and parent jobs were all significantly positively related to
children’s career aspirations. Compared to other studies, this study found stronger race and
gender effects on career aspirations. Age effects were also found to be stronger in this
study. Contrary to other studies suggesting a positive relationship between age and
aspirations, the individual correlations in this study showed that aspirations decreased with

age.

126

Unlike other studies suggesting a strongly positive relationship between community
characteristics and career aspirations, this study found mixed results. The individual
correlations found in this study revealed a positive relationship between community capital
and desired careers, but a negative relationship to expected careers. An examination the
individual correlations in this study suggest that much of the existing research on career
aspirations may be applicable to children living in poverty, yet important differences may
remain in terms of the impact of children’s background including age, race, gender, and
community socioeconomic status. However, these univariate comparisons are limited
because they are not taken into context of other variables. Therefore, it is important to

discuss the findings of the ecological model used in this study.

Usefulness of Ecological Model in Understandng Career Aspirations

Because of the limitations of univariate studies, this study was conducted to
understand the role of community, family, and child capital in the development of
children’s career aspirations. This was believed to be useful because earlier studies had
predominantly been limited to research on single variables as predictors of career
aspirations. Such limitations may have over or underestimated the role of any single
variable when not measured in the context of other factors related to career aspirations.
The present research highlighted the importance of including child, family, and community
factors as predictors of the prestige and earning potential of the jobs that children desire and
expect to achieve.

Consistent with the ecological model, human capital resources were transmitted

from the community to the child through the mother. The educational capital in the

127

 

—'" " -—-~— L...-............

community positively predicted mother’s educational capital, which in turn predicted
academic achievement of children. All of these relationships were moderate and similar in
strength. Similar to the way mother’s education levels predicted children’s academic
achievement, the socioeconomic status (SES) of mother’s most recent jobs had a strong
influence in the SES of children’s desired careers and a moderate influence on the SES of
the careers children expected to attain. For these children living in poverty, it was clear
that children’s resources were at least partially attributed to the resources of their mothers
and the community around them.

Also consistent with the ecological model, the most proximal influences were the
strongest predictors of children’s career aspirations. In other words, the human capital of
the mothers and children were stronger influences than community capital in predicting
career aspirations because of their close proximity to the developing child. By far, the
strongest and most direct influences on children’s career aspirations were the
socioeconomic quality of mothers’ jobs followed by children’s grades in school. The
socioeconomic statuses (SES) of mother’s jobs were strong predictors of the job SES of
children’s desired jobs and were moderate predictors of children’s expected career SES.
Similarly, the academic achievement of children was a strong predictor of the SES of the
jobs children desired to achieve and moderately related to the SES of the jobs that they
expected to attain.

Other forms of mother and child capital indirectly predicted career aspirations
although the effect was weaker than the direct influences. Children’s self-worth and
mother’s educational attainment indirectly had a small, but significant, positive impact on

children’s career aspirations. Mother self-worth was dropped from the model entirely, as it

128

did not predict any child or mother attributes. Although unemployment has been
associated with negative self-perceptions (Aubry, Tefft, & Kingsbury, 1990; Keefe, 1984),
there was no evidence that mother’s self-concept was related to the educational or
employment attributes of these women. This finding refutes the notion that negative self-
perceptions are potential factors in welfare dependency.

Weaker still were the indirect influences of community capital on children’s career
aspirations. The average educational level and job socioeconomic status of members of the
children’s community had a small, but significant, positive effect on children’s career
aspirations. This influence was similar for the careers children desired and expected.
Overall, mother and child capital were each stronger influences on children’s career
aspirations than community capital, yet all were significant. Furthermore, human capital in
the form of education and employment were stronger predictors of children’s career

aspirations than was psychological forms of human capital.

Comarison of Multivariate Results to Univariate Meta-Analysis Results

The multivariate model showed some important differences in results compared to
univariate results highlighted in the meta-analysis of existing literature on children’s career
aspirations (See Table 13). Univariate analyses have suggested that children’s acadenric
achievement and self-competence were strong predictors of career aspirations. Although
children’s grades remained a strong predictor of children’s career aspirations in this
multivariate model, children’s self-worth was found to be a weak predictor of career

aspirations when other variables were taken into consideration.

129

Univariate analysis also showed that parents’ jobs and educational background, and
community economic conditions were moderate predictors of career aspirations. Similar to
those findings, mother’s job SES was found to be a strong predictor of career aspirations in
this multivariate study. However, the impact of mother’s educational attainment and
community characteristics were found to be weaker when considered in relation to other
variables.

The multivariate ecological model utilized in this study provided important
information that has not been available in univariate studies. This model indicated that
children’s self-worth was less important than shown in other studies when other more
important variables were taken into account. These more important variables included
mother’s job SES and children’s academic performance. By using this multivariate
approach, this model revealed that community, mother, and child human capital remained
significant factors in children’s career aspirations when all were taken into account, and
that educational and employment capital were more important than psychological capital.
This finding suggests that access to capital and opportunities may be more important
factors than individual self-perceptions in the intergenerational transmission of poverty.
This finding provides some evidence to refute the notion that deficient individual attitudes

may be the cause of welfare dependency.

Reality and the Resilience of Children Living in Povem
In this study, children were found to have to have a high level of self-efficacy in
terms of their career plans. The socioeconomic statuses of the careers that children desired

to have were positively related to the socioeconomic statuses of the careers that children

130

 

expected to achieve. This coincided with other findings (Parmer, 1993) in which students
reported high levels of confidence and beliefs that they would work in their desired career.
Whether or not children in the present study desired and expected to have the same exact
career, the education and earning potential of the desired and expected jobs were related,
with children of black mothers having higher expectations than children of white mothers.
This suggests a high level of self-efficacy among the children in this sample. On the
whole, children expected to achieve the level of career they desired in terms of
socioeconorrric status.

This may point to the resilience of children living in these economic conditions
(Orthner, 1990; Werner, 1993) in that their goals have not been deterred by their present
circumstances. This self-efficacy is also evidenced by the fact that the average SES of the
jobs children aspire or expect to achieve are nearly double the average ratings of the SES of
jobs held by their mothers and their communities. Although these findings may point to
positive aspects of children’s resilience and self—efficacy, it does raise some concerns about
potential future disappointments.

Children living in poverty have been found to have strong beliefs that they will
have more opportunities to achieve a good career than other children living in poverty will.
In interviews with 5 to 13 year old children receiving AFDC assistance, children reporting
perceiving difficulties for children living in poor neighborhoods to get good jobs, but they
believed that their friends and they would be exceptions to the rule (Weinger, 1998).
Furthermore, when asked what types of jobs children in poor neighborhoods would prefer,
these children responded with careers that were lesser status jobs or glamorous jobs held by

role models. Such findings suggest that children from impoverished conditions may use

131

these coping mechanisms to maintain hope for their future despite difficult circumstances.
It may also reflect limited knowledge about attainable careers (as opposed to fantasy
careers) with decent wages (as opposed to lower paying jobs that they have been exposed
to in their community). Additional planning, information, education, and assistance may
be needed to help these children identify non-fantasy career goals and the steps needed to
attain these goals.

Previous studies of non-poverty children have shown that many children aspire to
achieve the same career type as their parents (See Table 9) and that children’s aspirations
are related to their future accomplishments (See Table 1). In this study, children’s job
desires were correlated with their mother’s jobs, yet children’s career desires far exceeded
those of their parents. Given these high expectations, it is not clear whether or not these
children will attain their desired careers at the same level as non-poverty children in other
studies. There is some evidence to suggest that lower SES children’s career aspirations
decreases over time (Gottfredson, 1981; Jacobs, Karen, & McClelland, 1991), especially in
the face of difficult life circumstances (Empson-Warner & Krahn, 1992). Therefore, more
research is needed to understand the developmental career process that children living in
poverty go through as they seek to enter their careers.

Overall, the findings from this study highlight the importance of an ecological
model of children’s career aspirations. The study partially supported many of the initial
hypotheses and demonstrated overall support for the transmission of capital from the
community, to the family, and to the child, ultimately influencing career decisions. The
quality of children’s career aspirations was directly predicted by their own academic

achievement, their view of their own self-competence, and the quality of jobs held by their

132

mothers. Although the effects were not as strong, the quality of children’s career
aspirations was indirectly influenced by the educational attainment of their mother’s and
the members of their community and the quality of jobs held by members of the
community. These findings have implications for future research and practice, despite the

lirrritations of this study.

Study Limitations

 

This study has some limitations in relation to the sample that should be noted. 7
Despite the numerous attempts to obtain participation of mothers and children in this study,
few of the original random sample chose to participate in the study. Comparisons of the
random sample to the study sample indicated that there were some differences between
those groups, with study participants having more resources than non-participants.
Therefore, results of this study may not generalize to all families receiving public
assistance, who may have even greater hardships than participants in this study. The
sample size was also smaller than desired, making it potentially difficult to detect
significant relationships in the path model. Therefore, the findings in this study may be
conservative and not include all significant findings. Additionally, participant, attrition
from the first interviews to the second interviews made it difficult toemploya
developmental perspective in the model since only wave one data was sufficient for
analysis of this model. The difficulty in obtaining a larger sample size is reflected by the
lack of inclusion of this sample in many other studies as well. Therefore, the limitations

associated with the small sample size should be weighed against the benefits of having any

133

data at all fiom this under-researched population. The findings of this study provide some

insights in future research and practice.

Implications for Practice

 

.;_:'These findings highlight the need for multi-level interventions for children living in
impoverished areas. Because individual and family-level variables were stronger than

__..-a-~‘"‘

community-level variables, community psychologists must consider whether the quantity
of people impacted by a community-level intervention would justify intervention at this
weaker lever of change. Although individual and family level interventions might be
stronger, it could be difficult to reach as many people as could be reached through a
community level intervention. In each case the quality of the intervention and the quantity
of impacted individuals must be considered at every level. Suggestions for interventions at
each level are suggested.

At the individual level, prevention efforts should aim to strengthen children’s
academic performance and help them to be aware of realistic careers that provide adequate
wages. At the same time prevention efforts must focus on the family and simultaneously
increase the educational and employment assets of the parent(s) so that these resources will
be available to stimulate children’s career development. At the community level
prevention efforts should focus on increase the quality of education available to children
and their parents and that this education can be translated into quality employment within
the area. Additional benefits are likely to be gained by passing federal legislation

mandating living wages for jobs so that more resources are available to children of families

presently considered working poor.

134

In these interventions, ethical considerations for individuals and communities must
be considered. Multi-pronged prevention efforts should be employed to simultaneously
invest in the career resources of children, their families, and their communities. Career
interventions focusing on the children may give them the tools to “escape their
surroundings.” This might help them to find gainful employment away from their home
communities, but may also encourage mass out-migration of local human resources. Such
out-migration can have negative impacts on the economic future of the community and its’
residents (Lichter, McLaughlin, & Comwell, 1993), and it can cause individual distress by
disrupting the social support available to individuals through their social networks (Elder,
King, & Conger, 1996).

On the other hand, the sole use of economic development interventions without
attention to the individual career development for those in poverty may also have negative
consequences. Economic development strategies that seek to develop or attract new
employment may not consider whether not it will produce quality paying jobs for the local
employees, or whether or not training will be provided for local residents that have not
already been integrated into the local workforce. There are also concerns that private
enterprises will co-opt the educational system in vulnerable communities and use the
system to create workers specifically designed for their companies, limiting the educational
future of youth in those schools. Thus, community economic development strategies and
individual career development strategies are simultaneously needed to improve individual
assets and the condition of employment available to families and their children. This must

be done so that individual career development does not come at the cost of the local

135

community, and that the needs of the community do not harshly restrict the choices of

individuals.

Future Research

 

Several areas of research may be needed to understand more about the career
development of this under-researched and economically vulnerable population. Overall, a
more developmental perspective is needed to follow these children over time to understand
their career progression. Because the children in this study may be at risk for
disappointment due to their high career expectations coupled with realistic barriers, it is
important to understand how their career aspirations change as they enter the work force
and encounter potential barriers. It is not clear whether or not the relationship between
career aspirations and career achievements is lower for children living in poverty compared
to middle and upper class children, but there is some evidence to suggest that this may be
true. Therefore, additional research should focus on predictors of actual career
achievements, rather than aspirations of children living in poverty.

Additional research may be needed to assess the impact of this model on more
diverse multi-ethnic populations given different family expectations for children’s career
plans (F uligni, Burton, Marshall, F ebles, Yarrington, Kirsh, Merriwether-DeVries, 1999).
Different aspects of families and communities are more salient to children’s career process
in different cultures and models need to be sensitive to these aspects. Aspects such as
respect for parent’s wishes and the subjugation of individual desires for the good of the
community or farrrily are important features of many families and may significantly impact

children’s career choices. Furthermore, appropriate measures must be developed and tested

136

within these different traditions. As noted in this and other studies, self-competence
measures normed on white populations have not been as reliable in non-white populations
(Pungello, Moore, & Campbell, 2000). Cultural competence is an important element that
should be attended to in these multivariate models.

In addition to research designed to better understand the developmental progression
of children’s career choice, the greatest need for research may be to evaluate the impacts of
action-oriented research designed to improve the career progression of children living in
poverty so that best practices can be identified. Future research is needed to evaluate such
multi-pronged interventions to improve the lot of both individuals and communities. Such
research should assess the impact of economic development efforts on the career
progression of the most economically vulnerable populations within those communities
where econorrric growth is occurring. Research may also be needed to assess whether or
not school-to-work partnerships are enhancing the career satisfaction of students, or
whether or not they are “tracking” students so that they fit the needs of the local labor
market at cost of individual choice. Additional research may consider the impact of career
mobility on the quality of life for individuals and their communities when students leave
home to pursue career goals. It is not clear to what extent this career advancement brings
additional economic resources back into the home community, and what long-term impact
this has on individual and commrmity social networks. From such research, it may be
possible to identify best practices so that education and economic policies can be defined to

produce the best mix of outcomes for individuals and their communities.

137

 

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153

Appendices

154

Appendix A — Child Self-Perception Profile Survey Questions

 

155

 

Child Self-Perception Profile Survey Questions (Harter, 1992)

 

Scholastic Self-Competence items: ql , q7,q13,q19,q25,q3l
Social Self-Competence items: q2, q8,q14,q20,q26,q32
Athletic Self-Competence items: q3, q9,q15,q21,q27,q33
Appearance Self-Competence items: q4, q10,q16,q22,q28,q34
Conduct Self-Competence items: q5, q11,q17,q23,q29,q35
Self-Worth Self-Competence items: q6, q12,q16,q24,q30,q36

 

We are interested in how you think and feel about different things. Since kids are very
different from one another, everyone will have different answers. I will read some

statements that tell about two kinds of kids. Please decide which kid you are most like.

Here is one example that talks about two kinds of kids: Some kids would rather play
outdoors in their spare time. Other kids would rather watch TV. I'd like you to decide
which kid you are more like. Are you more like the kid who would rather play outdoors, or
are you more like the kid who would rather watch TV.?

<1 FIRST KID

<2 SECOND KID

<8 DONT KNOW [goto Q2]

<9 REFUSED [goto Q2]
Next, I would like to know how true this is for you. Is that very true for you or only sort of
true for you?

<1 VERY

<2 SORT OF TRUE

<8 DONT KNOW
<9 REFUSED

156

 

The following questions used the same response format shown in the example above.

Q1

Q2

Q3

Q4

Q5

Q6

Q7

Q8
Q9

Q10

Q11
Q12

Some kids feel that they are very good at their school work. Other kids worry about
whether they can do the school work assigned to them.

Some kids find it hard to make friends. Other kids find it's pretty easy to make
friends.

Some kids do very well at all kinds of sports. Other kids don't feel that they are very
good when it comes to sports.

Some kids are happy with the way they look. Other kids are not happy with the way
they look.

Some kids often do not like the way they behave or act. Other kids usually like the
way they behave or act.

Some kids are often unhappy with themselves. Other kids are pretty happy with
themselves.

Some kids feel like they are just as smart as their classmates. Other kids aren't so
sure and wonder if they are as smart as their classmates.

Some kids have a lot of friends. Other kids don't have very many fiiends.

Some kids wish they could be a lot better at sports. Other kids feel they are good
enough at sports.

Some kids are happy with their height and weight. Other kids wish their height or
weight were different.

Some kids usually do the right thing. Other kids often don't do the right thing.
Some kids don't like the way they are leading their lives. Other kids do like the way

they are leading their lives.

157

Q13

Q14

Q15

Q16

Q17

Q18

Q19
Q20

Q21

Q22

Q23

Q24

Some kids are pretty slow in finishing their school work. Other kids can do their
school work quickly.

Some kids would like to have a lot more fiiends. Other kids have as many friends as
they want.

Some kids think they could do well at just about any new sports activity they have
not tried before. Other kids are afiaid they might not do well at sports they have not F
ever tried. I
Some kids wish their body was different. Other kids like their body the way it is.

Some kids usually act the way they know they are supposed to. Other kids often

 

don't act the way they are supposed to.

Some kids are happy with themselves as a person. Other kids are often not happy
with themselves.

Some kids often forget what they learn. Other kids can remember things easily.
Some kids are always doing things with a lot of kids. Other kids usually do things
by themselves.

Some kids feel that they are better than others their age at sports. Other kids don't
feel they can play as well.

Some kids wish their physical appearance, that is, how they look, was different.
Other kids like their physical appearance the way it is.

Some kids usually get in trouble because of things they do. Other kids usually don't
do things that get them in trouble.

Some kids like the kind of person they are. Other kids often wish they were

someone else.

158

Q25

Q26

Q27

Q28

Q29

Q30

Q31

Q32

Q33

Q34

Q35

Q36

Some kids do very well at their class work. Other kids don't do very well at their
class work.

Some kids wish that more people their age liked them. Other kids feel that most
people their age do like them.

In games and sports some kids usually watch instead of play. Other kids usually
play rather than watch.

Some kids wish their face or hair looked different. Other kids like their face and
hair the way they are.

Some kids do things they know they shouldn't do. Other kids hardly ever do things
they know they shouldn't do.

Some kids are very happy being the way they are. Other kids wish they were
different.

Some kids have trouble figuring out answers in school. Other kids almost always
can figure out the answers.

Some kids are popular with others their age. Other kids are not very popular.

Some kids don't do well at new outdoor games. Other kids are good at new outdoor
games right away.

Some kids think that they are good looking. Other kids think that they are not very
good looking.

Some kids behave themselves very well. Other kids often find it hard to behave
themselves.

Some kids are not very happy with the way they do a lot of things. Other kids think

the way they do things is fine.

159

Appendix B — Mother Self-Perception Profile Survey Questions

 

 

160

Adult Self-Perception Profile (Harter, 1985)

 

Global Self-Worth items: q8, q9, q10, q] 1
Job Self-Competence items: q12, q13, q14, q15

Provider Adequacy items: q16, q17, q18, q19

 

 

 

Sample question
Next, I will read some statements describing two kinds of people. For each, please tell me
whether you are more like the first person or the second person.
Some people are very happy being the way they are but other people would like to be
different. Are you more like the first person or the second person?

<1> FIRST PERSON

<2> SECOND PERSON

<8> DONT KNOW [goto Q9]

<9> REFUSED [goto Q9]

Now please tell me how true this is for you. Is that very true for you or only sort of true for
you?
<1> VERY TRUE
<2> SORT OF TRUE
<8> DONT KNOW
<9> REFUSED
The following questions used the same format as above.
Q9 Some people question whether they are a worthwhile person, but other people feel

sure that they are a worthwhile person.

161

Q10

Q11

Q12

Q13

Q14

Q15

Q16

Q17

Q18

Q19

Some people are disappointed with themselves but other peeple are quite pleased
with themselves.

Some people like the kind of person they are but other people would like to be
someone else.

Some people are not satisfied with the way they do their work but other people are
satisfied with the way they do their work.

Some people feel they are very good at their work, but other people worry about
whether they can do their work.

Some people are not very productive in their work but other people are very
productive in their work.

Some people are proud of their work but other people are not very proud of their
work.

Some people feel they are not adequately supporting themselves and those who are
important to them but other people feel they are providing adequate support for
themselves and others.

Some people are satisfied with how they provide for the important persons in their
lives but other people are dissatisfied with how they provide for these people.
Some people feel they cannot provide for the material necessities of life but other
people feel they do adequately provide for the material necessities of life.

Some people feel that they provide adequately for the needs of those who are
important to them but other people feel they do not provide adequately for these

needs.

162

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178

Appendix E - Prestige Scores of Mother’s Current/Most Recent Jobs at Time 1

 

179

 

Survey 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SiE§T=ZFatings
CASEID Most Recent Job rater 1 rater 2 ratejr3 Mean

10403 home chore prgvider 14.83 14.83 15.38 15.01
10494 CLEAN HOUSES. 15.71 14.83 15.38 15.31
10186 a housekeeper 15.38 15.38 15.38 15.38
10845 housekeeper 15.71 15.38 15.38 15.49
10341 Housekeeper 15.71 15.38 15.38 15.49
10796 Housekeeper 15.71 15.38 15.38 15.49
10107 housekeeping 15.71 15.38 15.38 15.49
10345 housekeeping 15.71 15.38 15.38 15.49
11169 housekeeping 15.71 15.38 15.38 15.49
10348 Housekeepigg 15.71 15.38 15.38 15.49
10123 Molly Maid. 15.71 15.71 15.71 15.71
10402 Chore Jrovider 18.12 14.83 15.38 16.11
11137 Sorted out nuts and bolts, counted

them and gut them in NIA 16.22 16.22 16.22
10517 Press operator 14.74 17.72 17.63 16.70
11159 crossing_guard. NIA 16.72 16.72 16.72
11012 Dry cleaning N/A 16.87 16.87 16.87
11132 worked in a Greenhouse N/A 16.88 16.88 16.88
10451 Chore provide and ajanitor 18.12 18.12 15.38 17.21
10019 punch press operator 14.74 19.37 17.63 17.25
10746 corn detasserling 17.75 17.09 17.09 17.31
10219 Seamstress 18.42 19.1 14.97 17.50
10433 Seamstress 18.42 19.1 14.97 17.50
10483 cook 17.54 17.54 17.54 17.54
10581 cook 17.54 17.54 17.54 17.54
10362 Burger Kingburger maker 17.75 NIA 17.54 17.65
11101 bus cleaner 17.24 NIA 18.12 17.68
10085 Am home health aid - fixed clients

meals, did grocery shopping, 14.83 14.83 23.58 17.75
10837 Made pizza and placed pepperoni and

cheese on pizza 17.75 17.75 17.75 17.75
10945 Worked at catering company - packed

food 17.75 17.75 18.33 17.94
10181 babysittirg 17.98 17.98 17.98 17.98
11161 pots and pans cleanirg 17.75 18.33 18.33 18.14
10409 Assembly line worker 18.81 17.88 17.88 18.19
10416 worked at housekeeping at the

Kalamazoo Hilton _ 23.55 _ 15.71 15.71 18.32
11115 I was on a assembly line Floor

Manufacturing 18.81 19.23 17.88 18.64
11071 I work with a glue gun. Working on

doors. Assembly line. 18.81 19.23 17.88 18.64
11149 factory work NIA 18.81 18.81 18.81
10282 hostess at a restaurant NIA NIA 18.88 18.88
10029 restaurant waitress, (A0) 18.88 18.88 18.88 18.88
10774 WAITRESS 18.88 18.88 18.88 18.88
10023 Waitress 18.88 18.88 18.88 18.88
10066 Waitress 18.88 18.88 18.88 18.88

 

180

 

Survey 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SfSTfiatings
CASEID Most Recent Job rater 1 rater 2 rater 3 Mean

11186 Waitress 18.88 18.88 18.88 18.88
11177 WAitress 18.88 18.88 18.88 18.88
10867 Waitressig; and cashier. 18.88 18.88 18.88 18.88
10772 Labor 18.81 19.23 18.81 18.95
10435 Factory Cafeteria prepared dinners. 17.75 18.33 20.8 18.96
10846 work preparing food and mnning a

register at Taco John's 20.8 17.75 18.33 18.96
10309 Works in shops to make tags for

machines about safety hazards N/A 18.7 19.37 19.04
10460 Office cleaning 18.2 18.12 20.79 19.04
10881 screw machine operator. 18.7 19.3 19.37 19.12
10215 Work in food service 20.8 18.33 18.33 19.15
10372 Folding diapers N/A 19.23 19.23 19.23
10807 folding diapers NIA 19.23 19.23 19.23
11024 Machine operator in factory 19.37 19.37 19.37 19.37
11148 machine operator 19.37 19.37 19.37 19.37
10743 fast food 17.75 20.8 20.8 19.78
10667 Passing seat belts NIA 20.77 18.81 19.79
10776 Binding ina print shop 19.86 19.86 19.86 19.86
10363 Fast food - cashier 17.75 20.8 21.4 19.98
10247 Thorn Apple Valley - exporting hams -

skin on skin machine NIA 18.86 21.17 20.02
10566 worked at a cleaners 26.49 16.87 16.87 20.08
10969 Making the starter for the car 18.81 20.77 20.77 20.12
11134 Manufacture car parts 18.81 20.77 20.77 20.12
10795 In a meat factory 18.81 21.17 21.17 20.38
10631 steel grinder NIA 22.09 18.88 20.49
10420 Custodial 18.2 25.37 18.12 20.56
10042 Care for an elderly woman NIA 17.83 23.58 20.71
10284 Deli work, counter work at schools 20.8 20.8 20.61 20.74
10841 deli work 20.8 20.8 20.61 20.74
10222 Counter-help NIA 20.8 20.8 20.80
10600 Food service AT WEndy's 20.8 20.8 20.8 20.80
10352 worked at Wendys 20.8 20.8 20.8 20.80
10244 cashier at Burgerflg. 21.4 20.8 20.8 21.00
10405 assistant supervisor for a cleaning

depatment, (Ao) 20.97 21.41 20.79 21.06
11188 cashier at Meijer's 21.4 ~ 21.4 20.8 21.20
,10063 production, shipping and recieving and

packagi_ng N/A 23.07 19.56 21.32
10480 lunch monitor N/A 19.37 23.38 21.38
10503 cashier 21.4 21.4 21.4 21.40
10522 cashier. 21.4 21.4 21.4 21 .40
10981 cashier. 21.4 21.4 21.4 21.40
10139 cashier 21.4 21.4 21.4 21 .40
10182 cashier 21.4 21.4 21.4 21.40
10311 cashier 21.4 21.4 21.4 21 .40
10113 Cashier 21.4 21.4 21.4 21 .40

 

181

 

 

Survey 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SES Ratings
CASEID Most Recent Job rater 1 rater 2 raté 3 Mean

10315 Cashier 21.4 21.4 21.4 21 .40
10464 Cashier 21.4 21.4 21.4 21.40
11077 Cashier 21.4 21.4 21.4 21 .40
10980 Cashier 21.4 21.4 21.4 21 .40
10229 cashierclerk 21.4 21.4 21.4 21 .40
11112 I run the register in a pharmacy 21.4 21.4 21.4 21 .40
10642 Worked in a comer store cashier 21.4 21.4 21.4 21 .40
10906 Works at Kmart as cashier and

supervisor 21.4 21.4 21.4 21 .40
10087 grocery store cashier 21.4 21.46 21.4 21.42
11043 Light industrial NIA 23.55 19.37 21.46
10414 child care. 23.55 23.55 17.98 21.69
10988 childcare. 23.55 23.55 17.98 21.69
10546 Tele operator 21.89 21.89 21.89 21 .89
10370 deliver Egazines NIA 23.07 21.1 22.09
10784 Delivery driver N/A 23.07 21.1 22.09
11104 watch kids...lunch lady. N/A 20.8 23.38 22.09
10038 rivate duty in home care 14.83 28.38 23.58 22.26
10160 Cab driver 22.46 NIA 22.46 22.46
10033 limousine, don't remember 22.46 22.46 22.46 22.46
10114

Bakeg - cashier counter help, baking 25.83 20.8 20.8 22.48
10340 Clerk at gas station 25.83 21.4 21.4 22.88
10991 child care service in the daycare 23.55 23.55 23.55 23.55
10024 Day care, Greeting card merchandiser,

and _. 23.55 23.55 23.55 23.55
10012 Day CARE 23.55 23.55 23.55 23.55
10695 Daycare worker 23.55 23.55 23.55 23.55
11125 Licensed in daycare. 23.55 23.55 23.55 23.55
10998 work with children in a day care 23.55 23.55 23.55 23.55
10948 CNA...certfied nursing assistant. 23.58 23.58 23.58 23.58
10733 nurse's Aid 23.58 23.58 23.58 23.58
10440 nurses aid 23.58 23.58 23.58 23.58
10723 nurses aid 23.58 23.58 23.58 23.58
11048 nurses aide 23.58 23.58 23.58 23.58
11023 Nurses aide 23.58 23.58 23.58 23.58
10297 nursing aid 23.58 23.58 23.58 23.58
10443 Registered nurse's aid 23.58 - 23.58 23.58 23.58
10272

Worked with mentally retarded adults NIA 23.58 23.58 23.58
11103 bartender. 23.96 23.96 23.96 23.96
10323 Bartender. 23.96 23.96 23.96 23.96
10206 Bartender 23.96 23.96 23.96 23.96
11065 I watched stores—a security guard. 24.17 24.17 24.17 24.17
10241 nurses assitant 23.58 25.96 23.58 24.37
10748 Nursingfiassistant for Tender Care 23.58 25.96 23.58 24.37
10571 student nurse 23.58 NIA 25.21 24.40
10585 veterinary assistant NIA 25.96 23 24.48

 

182

 

Survey 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

matings
CASEID Most Recent Job rater 1 rater 2 rate; 3 Mean

10597 selling hams. 26.49 25.83 21.4 24.57
10054 Medical Billing 24.72 24.72 24.72 24.72
10153 Production Typist. 25.22 25.22 25.22 25.22
10647 telemarketer 28.6 25.37 21 .89 25.29
10744 hung up clothes at the good will NIA 25.37 25.37 25.37
10334 Retail 25.83 25.83 25.38 25.68
10259 sales clerk 25.83 25.83 25.38 25.68
10690 Sales person at a store 25.83 25.83 25.38 25.68
10046 sales person 25.83 25.83 25.38 25.68
11109 Sales 25.83 25.83 25.38 25.68
10120 Salesperson 25.83 25.83 25.38 25.68
11084 Worked with husband at party store N/A 25.83 25.83 25.83
10606 data entry, clerical 31.26 23.33 23.33 25.97
10025 mail room clerk 26.16 26.16 26.16 26.16
10426 Various, (more specific), fixed motor

parts, assembling N/A 20.95 31.45 26.20
10406 work as a customer service specialist

at McDonalds 20.8 25.37 32.72 26.30
10049 Worked at Print shop N/A 26.35 26.35 26.35
10083 Locker Room attendant for city of

Detroit Parks and Recreation. NIA 23.91 28.91 26.41
10374 File clerk 25.83 28.92 24.98 26.58
10957 Noon Hour Aide at the school NIA 31.57 23.38 27.48
10449 playground supervisor for Vicksburg

school system N/A 31 .57 23.38 27.48
11140 Desk Clerk 25.83 28.92 29 27.92
10651 Zoned mail 30.25 N/A 26.16 28.21
10059 EMT, emergency medical technicia NIA 28.76 28.76 28.76
10226 General office with a little sales NIA 28.92 28.92 28.92
11167 Mostly clerical 28.92 28.92 28.92 28.92
10496 Electronics N/A 28.95 28.95 28.95
10171 customer service and data entry N/A 25.37 32.72 29.05
10069 Customer service NIA 25.37 32.72 29.05
11123 clerical work 25.83 28.92 32.41 29.05
10150 clerical 25.83 28.92 32.41 29.05
10228 Clerical 25.83 28.92 32.41 29.05
10108 diet clerck 25.83 28.92 32.72 29.16
10886 bank Teller 29.33 29.33 29.33 29.33
10088 Bank 29.33 29.33 29.33 29.33
10050 worked on a doctor‘s office 28.92 28.92 32.41 30.08
11045 United States Air Force (aircraft

maintenance.) 28.76 30.85 30.78 30.13
11 180 Accounting 30.43 30.43 30.43 30.43
10308 Book keeping 30.43 30.43 30.43 30.43
10035 Bookkeeflg at office 30.43 30.43 30.43 30.43
10965 word processing. N/A 25.22 36.84 31.03
10015 I'm an aid for the LeamMenter. NIA 31 .57 31 .57 31 .57
10767 Read to Children(tutor). N/A 31.57 31.57 31.57

 

183

 

Survey 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SES Ratings
CASEID Most Recent Job rater 1 rater 2 rater 3 Mean

10304 tutor N/A 31 .57 31 .57 31 .57
11146 tutored NIA 31 .57 31 .57 31 .57
10303 work at the school. N/A NIA 31 .57 31 .57
10193 Financial Aid Assistant N/A 32.41 32.72 32.57
10777 Sales job seIILng books (?) 25.83 46.25 26.49 32.86
10495 medical assistant 25.96 50.75 23.58 33.43
10200 supervisor inspectress 37.07 43.68 22.03 34.26
10999 I was a secretary for the Psychiatry

Dept. for a hospital. I did 34.73 34.73 34.73 34.73
10583 Scretarial 34.73 34.73 34.73 34.73
10876 secretarial 34.73 34.73 34.73 34.73
11189 Secretarial 34.73 34.73 34.73 34.73
10248 secretary. 34.73 34.73 34.73 34.73
10428 Secretary 34.73 34.73 34.73 34.73
11110 Collect money for audit companyu NIA 35.41 35.41 35.41
10318 reimbursements for the county N/A NIA 35.41 35.41
10395 Mappingfiompany. Scriber NIA 39.43 32.41 35.92
10040 Cut negatives, got portraits ready NIA 42.86 29.19 36.03
10173 Supervisor at a bank 37.07 36.87 36.87 36.94
10778 Sales Management 25.83 48.1 51.96 41.96
10007 Dietician at a Day care center N/A 43.38 43.38 43.38
11178 phlebotomist 54.96 44.63 44.63 48.07
11105 manager Salvation Army. 48.1 48.1 51.96 49.39
10481 substitue teacher. N/A 52.99 52.99 52.99
1 1 184 teacher N/A 52.99 52.99 52.99
10130 Electronic TRW. NIA 78.97 28.95 53.96
10441 Make decorative vases 54.42 54.42 54.42 54.42
10994 Systems Analysis at Ford Motor

Company. NIA 64.94 73.06 69.00
10535 Rackies NIA N/A NIA NIA
10207

Works at same job as indicated before NIA N/A N/A N/A

 

184

 

Appendix F — Confirmatory Factory Analysis Results for Harter Child Self-Perception

 

Profile

185

 

 

Item-Factor Loading

on expected factor)

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Item # Description 171—5-153—- F4 133—1?
1 Good at school work 0.83 0.57 0.16 0.33 0.52 0.62
8 7 Smart as classmates 0.22 0.30 0.80 0.19 0.14 0.84
‘_ {5‘2 E 13 Quick at school work 0.34 0.06 0.30 0.72 0.46 0.37
25 g g 19 Rememberthings easily 0.45 0.10 0.21 0.56 0.96 0.47
s 2 E 25 Do well at class work 0.47 0.40 0.64 0.47 0.42 1.05
E 0’ 8 31 Easy to figure answers 0.27 0.45 0.38 0.24 0.37 0.55
0 2 Easy to make friends 0.23 0.60 0.89 0.13 0.01 0.26
'g 8 8 Lot of friends 0.23 0.37 0.44 0.72 0.04 0.26
a 3:3 14 Have enough friends 0.30 0.24 0.24 0.16 0.87 0.54
.5 a 20 Usually with others 0.25 0.42 0.13 0.29 0.32 1.10
1'5 E 26 Feel liked 0.21 0.40 0.32 0.36 0.24 0.30
E 8 32 Popular with peers 0.54 0.35 0.29 0.26 0.35 0.36
3 Good at sports 0.26 0.18 0.94 0.63 0.23 0.31
8 9 Good enough at sports 0.21 0.39 0.28 0.33 0.74 0.39
m g 15 Do well at new sports 0.26 0.22 0.39 0.25 0.30 1.02
8 .3, g 21 Better at sports than peers 0.60 0.37 0.19 0.23 0.17 0.61
t; g g 27 Rather play than watch sports 0.28 0.55 0.13 0.22 0.16 0.28
if E o 33 Good at new outdoor games 0.52 0.43 0.29 0.28 0.40 0.50
4 Happy with looks 0.24 0.21 0.16 0.34 0.64 0.42
0 10 Happy about height/weight 0.16 0.10 0.11 0.50 0.14 0.75
v _ g 16 Like bodythe wayitis 0.65 0.10 0.35 0.27 0.33 0.28
6' g :5 22 Like appearance the wayitis 0.14 0.37 0.75 0.35 0.21 0.41
1'5 ‘9. 8 28 Like face the way it is 0.35 0.60 0.27 0.46 0.29 0.54
u“: E 5% 34 Think good looking 0.66 0.42 0.33 0.33 0.27 0.39
5 Like way behave 0.25 0.27 -0.010.11 0.47 0.86
_ 11 Do the right thing 0.76 0.23 0.00 0.23 0.41 0.27
m g ‘6' 17 Act way supposed to 0.26 0.06 0.50 0.77 0.19 0.21
6 '5 a 23 Don't get in trouble 0.32 0.34 0.71 0.22 0.26 0.41
13 .2 E 29 Don't things shouldn't 0.40 0.60 0.49 0.23 0.49 0.56
if 3 8 35 Behave well 0.58 0.27 0.39 0.37 0.48 0.51
6 Happy with self 0.69 0.34 0.38 0.23 0.23 0.26
if; 12 Like the way leadifl life 0.33 0.40 0.46 0.24 0.57 0.03
g 18 Happy with self 0.33 0.20 0.30 0.90 0.24 0.51
.5 c 24 Like self 0.41 0.25 0.49 0.48 0.46 0.42
is E 30 Happy with the way things are 0.51 0.63 0.44 0.20 0.41 0.17
if 3 36 Happy with how they do things 0.55 0.37 0.52 0.24 0.36 0.46
FLactor1 1 1.00 »
Factor2 0.73 1.00
. Factor3 0.97 0.97 1.00
"em'Facm'madm Factor4 0.98 0.80 0.88 1.00
Fact0r5 1.12 0.77 0.91 0.84 1.00
Factor6 1.52 1.18 1.40 1.24 1.23 1.00
Average correlation within factor 0.18 0.16 0.12 0.14 0.14 0.09
Standard score coefficient alphas 0.56 0.53 0.46 0.49 0.50 0.37

 

 

 

 

 

 

186

AJpendix G - Exploratory Factory Analjsis Results for Harter Child Self-Perception

Profile

187

 
 

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189

Appendix H — Confirrnatory Factory Analysis Results for Harter Adult Self-Perception

 

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192

 

 

   

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