Ethnic Culture: Understanding the Preconditions

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Youth & Society
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DOI: 10.1177/0044118X10382030
Youth Society 2011 43: 1136 originally published online 4 October 2010
Leticia Oseguera, Gilberto Q. Conchas and Eduardo Mosqueda
for the Potential Realization of Social Capital
Beyond Family and Ethnic Culture: Understanding the Preconditions
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Youth & Society
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1
Penn State Department of Education Policy Studies
2
UCI Department of Education
3
UCSC Department of Education
Corresponding Author:
Leticia Oseguera, Pennsylvania State University Department of Education Policy Studies, 400
Rackley Building, University Park, PA16802
E-mail: [email protected]
Beyond Family and
Ethnic Culture:
Understanding the
Preconditions for the
Potential Realization
of Social Capital
Leticia Oseguera1
, Gilberto Q. Conchas2
,
and Eduardo Mosqueda3
Abstract
This article extends our conceptual understanding of social capital and
school achievement through a comparative race and ethnic approach. Using
the National Educational Longitudinal Study (NELS) 1988-1990 panel, this
article develops a more comprehensive understanding of school achievement
by exploring circumstances, which the authors call “preconditions,” leading
to the potential for the realization of social capital. These “preconditions” are
used to explain academic engagement disparities between Southeast Asian,
Black, Mexican, and White high school youth. Whereas previous research on
social capital leaves the mechanism through which social capital influences
school outcomes unspecified, this study focuses on a behavior associated
with positive educational outcomes—time per week spent on homework
outside of school. Although preconditions for parental capital appear to have
some influence on students’ study behavior, so too do preconditions between
and within schools, such as peers and teachers. This research shows that
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Oseguera et al. 1137
relationships outside the family—that is, within and between school opportunities for social capital—play a significant role in explaining variation between
the four ethnic groups.
Keywords
academic engagement and achievement, school context, social capital
Introduction
Unequal resources generate disparity in school engagement and achievement. These resources may be evident, such as financial support, school
infrastructure, and technology, or less tangible, such as norms, encouragement, and information gained from relationships and social networks.
Social capital is described as the less tangible resources gained through
social relationships that positively influence educational outcomes
(Coleman, 1988a). It is defined by its function and framed around the
value of social networks that contribute to beneficial outcomes (Coleman,
1988a; Uslaner, 2001). Nuanced and complex, social capital must be conceptualized as multidimensional to have any useful explanatory significance (Day, 2002).
Access to high-quality social capital is invoked to explain the educational
engagement and achievement of students. It has been used to explain students’ math achievement scores (Morgan & Sorensen, 1999), grade point
averages (Valenzuela & Dornbusch, 1994), and low school drop-out rates
(Astone & McLanahan, 1991; Carbonaro, 1998). Although social capital has
a wide-ranging definition and has been characterized in several different
ways (Bourdieu, 1977, 1986; Burt, 1992; Portes, 1998), sociologists who
study education often base their research on the work of Coleman (1988a),
which focuses on the information, support, and supervision provided by
closely knit networks of relationships. Coleman notes that both the sum of
relationships and the interconnectedness of those relationships affect children’s educational outcomes.
In this study, we use the social capital framework employed by Coleman
(1988a, 1988b) to select measures that best reflect circumstances in students’ environment offering the potential to realize social capital. We consider these circumstances preconditions for the potential realization of social
capital. Thus, we do not employ the term “social capital” in its literal sense,
as social capital only becomes true capital when activated or converted. In
other words, we expand how we think of this concept by measuring the
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1138 Youth & Society 43(3)
various preconditions that allow the application of social capital to the real
world. For example, student–teacher interactions in and of themselves do
not reflect social capital unless we can also show that these interactions
produce some later benefit for the student. It is this presumption of a future
benefit or privilege that we use in our conceptualization and design of this
study. We argue that, in order to further explain the complexity of academic
engagement and achievement among ethnic groups, we must first conceptually unpack the in-school and out-of-school preconditions for the realization
of social capital.
Preconditions for the Realization of Social Capital
Many researchers who study the subject consider the family to be a child’s
most important supplier of social capital. Following Coleman, research on
this subject focuses on the influence that parents, through their connections
with children, schools, and other parents, have on the educational achievement of the general school population (e.g., Coleman, 1988b; Mehan,
Villanueva, Hubbard, & Lintz, 1996). Thus far, research on children’s social
capital has been less concerned with sources outside the home, that is,
social capital that comes from schools and relationships with peers.1
However, children spend large portions of their days in settings without
their parents. Potential sources of “within and between school” social
capital activators include friends, teachers and other school officials, as
well as communities. Ignoring these potential sources of social capital is
problematic, as discrepancies in children’s educational outcomes are attributed solely to the actions of parents, while school and community practices
are left unexamined (Conchas, 2001, 2006; Feliciano, 2006a, 2006b; Goyette
& Conchas, 2002).
Coleman’s (1987) original conception of social capital does not account
for power, inequality, or privilege. This limitation may leave researchers with
an incomplete understanding of how this resource, particularly as it relates to
privilege and opportunity, operates among students. Stanton-Salazar and
Dornbusch (1995), for example, contend that children from low-SES and
minority families make use of information and support from peers and institutions even more than of that provided by families. In fact, research has
found that recently immigrated parents may be ill equipped to provide their
children with information about the U.S. educational system, and minority
parents may feel alienated from it (Feliciano, 2006a; Gandara & Contreras,
2009; Valenzuela, 1999). In other words, children may not always be able to
rely on parents for the resources they need to succeed.
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Oseguera et al. 1139
In this article, we have chosen Southeast Asian Americans,2
African
Americans/Blacks, Mexican Americans/Mexicans, and Whites, four groups
with disparate academic performances traditionally attributed to family relationships, to illustrate the significance of within and between school opportunities for the realization of social capital. Both the Southeast Asian and
Mexican groups are composed of many first- and second-generation immigrants and tend to be less English proficient and of lower SES than Whites,
but they present disparate educational outcomes. Southeast Asian students
maintain better grades, graduate from high school at higher rates, and enroll
in college more than the other three student groups (Conchas, 2006).
A popular explanation for these differences is that Asian families promote
children’s success by emphasizing Confucian values (Caplan, Choy, &
Whitmore, 1991; Nash, 1987). Some speculate that a tightly knit family
demanding a child’s full loyalty and attention limits the commitment a child
of Mexican origin can make to his education (Carter & Segura, 1979;
Chavez, 1992). Traditional research examining the educational achievements of the four groups selected for this study asserts that the norms conveyed through family social capital account for students’ school success or
failure. Recent research, however, shows that it may be as or more important
to consider the resources Asian students gain, in particular, from parents’ premigratory educational and postmigratory socioeconomic status (Feliciano,
2006a), as well as resources gained from relationships in schools (Conchas,
2001, 2006; Stanton-Salazar, 2001), in accounting for disparities between
the groups.
In this article, we compare circumstances in two settings providing sources
of nonfamilial social capital. First, we examine macroinstitutional conditions
reflecting inequality among schools (i.e., between school preconditions for
social capital). Evidence concerning the impact of the school environment on
a student’s motivation and achievement is mixed. After controlling for
parental SES levels, many researchers find minimal effects of school context
on students’ achievement (Catterall, 1998; Rumberger, 1987; Thornton &
Eckland, 1980), whereas others find that students who attend schools with a
predominantly low-SES population and high concentrations of minorities
have less accurate information about educational and occupational opportunities (Conchas, 2006; Kemple & Snipes, 2000; Stanton-Salazar & Dornbusch,
1995). Schools with higher concentrations of students of color generally
offer fewer advanced curriculum courses and have lower test scores, higher
drop-out rates, less financial resources, and a host of other negative factors
that contribute to lower student success (Orfield & Lee, 2005, 2006).
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1140 Youth & Society 43(3)
Our research shows significant differences in this setting between the
groups selected.
Our second research setting is found within the schools themselves (i.e.,
within school preconditions for social capital). Students in the same schools
may maintain different relationships with peers, teachers, and other school
officials. Conchas, for instance, found these relationships can be conceived
as sources of social capital because peers and teachers provide encouragement, support, supervision, and information to the student. Also, teachers
tend to encourage students whom they believe are talented or hard working
(Farkas, Grobe, Sheehan, & Shuan, 1990; Stanton-Salazar, 2001). Principals
and guidance counselors may provide data about college preparation courses,
applications, and financing for students without access to these data at home.
Guidance counselors may take students on trips to colleges to help them
make informed choices. Education personnel may choose students whom they
believe worthy to “sponsor” and thus enable their educational achievement
(Conchas, 2006; Mehan et al., 1996).
Another important source of within school preconditions for social capital
is academic tracking. Research on low- or high-track placements has illuminated unequal opportunities for learning as a result of differences in access to
challenging curriculum, student expectations, and well-prepared teachers
(Lucas, 1999; Oakes, Gamoran, & Page, 1992). Such inequities were found
to disadvantage students in low tracks and advantage students in high tracks.
Our findings also confirm past research, which documents greater access to
and enrollment in advanced placement or honors courses by Asian and White
students than by Black and Mexican students (Oakes, 1985, 2005).
The effects of peers on students’ academic behaviors are well known.
Educational research has long stressed how students’ interactions with one
another and the meanings associated with these interactions significantly
shape patterns of academic behavior. Scholars posit that the peer group can
serve as a mediating factor, either promoting compliance with or resistance
to a school’s rules for success (Conchas, 2006; Lee, 1996, 2005; Mehan,
Hubbard, & Villanueva, 1994). For example, students with many friends who
drop out of school may be negatively influenced to do the same (Conchas,
2006; Fine, 1991; Vigil, 1988). In addition, these students are unlikely to
receive support and encouragement from drop-out friends to study, and these
friends are unlikely to have academically useful information.
In contrast, students whose friends consider studying important are likely
to have support, encouragement, and information that motivate and enable
them to study hard. Steinberg, Brown, and Dornbusch (1996) further assert
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Oseguera et al. 1141
that, although peer groups are an important influence on all students’ educational outcomes, for some racial groups peers are an even more important
influence than parents. As a matter of fact, research shows that Asian Americans,
who often associate with other high-achieving Asian American students, get
most of their information, norms, and support from peers (Conchas & Perez,
2002; Lee, 1996).
In this article we explore how socioeconomic differences, gender, and
both the familial and between- and within-school settings affect preconditions for the realization of social capital and help explain the variation in time
spent doing homework outside of school. Our results indicate that not only
the involvement of families but also preconditions for social capital realization available to students outside the home account for the differences in
study habits. Parental expectations and the potential acquisition of social
capital within and between schools both shape the educational habits of
youth, which are, in turn, heavily influenced by a parent’s SES.
Time Spent on Homework Outside of School
Unlike other research on social capital, this article measures the effects of
preconditions for the realization of social capital on the time 10th-grade
students spend on homework outside of school per week, a behavior that
many believe is associated with positive educational outcomes (Corno, 1993;
Walberg, 1991).
We selected hours per week spent on homework because past research has
demonstrated that this is a strong indicator of school achievement (Adelman,
2006; Coleman & Hoffer, 1987; Zimmerman & Schunk, 1989). Betts (1997)
and Walberg (1991) separately found that homework time had a large effect
on academic achievement. Using data from the High School and Beyond
1980 cohort, Sander (2000) found that, among Black and Hispanic Catholic
school attendees, hours spent on homework had a positive effect on test
scores. Other research supports the effect of homework on a variety of academic and behavioral characteristics, including study skills (Zimmerman &
Schunk, 1989), reducing disruptive behavior, and bringing positive attitudes
to task (Corno, 1994). In a review of research on the efficacy of homework
and her own experimental designs of adolescents and homework behavior,
Corno concluded that “what students take from doing homework includes
knowledge and skills stretched across the home-school environment, interpersonal and self-regulation styles, and mannerisms, and an identification
with an academic and social community of others who do homework” (Corno,
2000, p. 545).
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1142 Youth & Society 43(3)
Data and Methods
Quantitative methods are used in this study to address the following research
questions:
Research Question 1: How do familial preconditions for the realization
of social capital explain study behavior differences between Southeast Asian, Black, Mexican, and White high school students?
Research Question 2: How do within- and between-school preconditions for the realization of social capital explain study behavior differences between Southeast Asian, Black, Mexican, and White high
school students?
Sample
Data are drawn from the National Educational Longitudinal Study (NELS)
1988-1990 panel, collected for the National Center for Education Statistics
(NCES) by the National Opinion Research Center. In 1988, the NCES surveyed 24,599 U.S. eighth graders whose responses were weighted to represent the population of eighth graders nationally. These same respondents
were resurveyed in 1990. Information was collected from the sampled students and their parents, teachers, and school administrators. The final sample
for this study included 167 Southeast Asian students, 1,233 Mexican students, 1,532 Black students, and 11,568 White students attending public,
religious, and private high schools throughout the United States. Data are
weighted using panel weights provided by NELS to reflect the responses of
all U.S. students who were 8th graders in 1988 and subsequently 10th graders in 1990. To minimize further reductions in sample size due to secondary
school dropouts, analyses were restricted to the 1988/1990 panel (Rumberger,
1987; Rumberger & Lim, 2008). For this reason, results can only be generalized to students who were 8th graders in 1988 and who were enrolled as 10th
graders in 1990.
Variables in the Analyses
Outcome variable. Our main outcome of interest is time spent on homework outside of school during an average week in the 10th-grade year. Using
a categorical scale, students were asked to report the amount of time spent
during an average week on homework outside of school. The categorical
variable was rescaled to represent whole-hour increments to facilitate
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Oseguera et al. 1143
interpretation. Subsequently, an interval level response3
was created where
students reported as low as 0 hours and as high as 18 hours of homework
outside of school in an average week.
Background and demographic variables. Demographic variables, including
gender, immigrant generation status, home language background, and SES
distribution, are included as controls in all multivariate models (see Table 1
and Appendix A for variable scaling).
Familial social capital variables. In order to capture potential familial capital,
we included measures of family composition (e.g., two-parent vs. one-parent
settings), parent–child and parent–school interactions.4
Parent–child interactions included how often parents spoke to their children about school experiences, high school and post–high school plans. For multivariate analyses,
these three measures were combined in a summary index, with each component weighted using the principal components analysis method.
We measured parent–school interactions with an index composed of four
variables. These variables account for whether parents volunteered at the
school, attended a school event, joined the parent teacher association (PTA),
or attended a PTA meeting.5
For multivariate analyses, all four measures
were combined in a single index (if a parent answered “yes” to any of the
questions, the parent was scored “1”). Another commonly used dimension of
familial capital is social closure. In this study, we measured closure by the
number of the child’s friends’ parents that a parent knows. Finally, parents
were also asked what their academic expectations for their children were (see
Table 1 and Appendix A for variable scaling).
Between-school variables. In order to capture the between-school context,
we included a number of preconditions for between-school social capital
measures obtained from school records such as percent of students receiving free or reduced lunch,6
percent of 10th graders who drop out of school,7
percent of students who continue on to a 4-year college, percent of parents
who volunteer at the school, school type (e.g., public), and racial/ethnic
distribution of the student body (see Table 2 and Appendix A for variable
scaling).
Within-school variables. The within-school social context measures included
in this study incorporate students’ high school academic program (e.g., academic vs. general), students’ assessments of the quality of the teaching at
their school, students’ perceptions of their favorite teacher’s expectation for
their academic success, as well as how many of the students’ peers dropped
out of school and their perceptions of the importance of studying to their
friends (see Table 2 and Appendix A for variable scaling).
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1144 Youth & Society 43(3)
Table 1. Selected Demographic, Socioeconomic, and Familial Capital
Characteristics by Ethnicity: NELS 1988-1990 Panel
Southeast
Asian Black Mexican White
Demographic and socioeconomic characteristics
Immigration generationa
First-generation (vs. second or third
generation)
82.1 2.9 24.8 2.4
Home language background
English dominant (vs. non–English
dominant)
41.3 98.0 41.8 97.7
SES (socioeconomic status) distribution
Lowest 25% quartile 38.9 37.6 56.3 15.5
Middle 50% quartile 45.3 51.0 37.7 53.1
Highest 25% quartile 15.8 11.5 6.0 31.4
Father’s education
Less than high school 29.4 19.1 49.8 11.9
High school graduate 40.7 62.5 41.5 55.5
College graduate 29.9 18.4 8.7 32.6
Preconditions for familial capital
Parents’ educational expectations for child
High school graduate or less 5.1 6.8 9.6 5.8
Two-year/ vocational college 6.9 13.0 17.1 14.2
Attend 4-year college 5.3 9.9 9.9 10.2
Graduate from a 4-year college 82.8 70.2 63.3 69.8
Family composition
Two parent (vs. single parent) 73.3 40.5 72.8 70.5
Talk to child about school experiencesb
Regularly (vs. not regularly) 48.6 78.1 66.6 82.8
Talk to child about high school plansb
Regularly (vs. not regularly) 39.6 57.5 51.1 44.5
Talk to child about post–high school plans
Regularly (vs. not regularly) 29.7 52.1 43.1 35.3
Mean Parent–Child Interaction Indexb
SD 3.6 (1.1) 4.4 (0.9) 4.0 (1.2) 4.2 (0.9)
Belong to the PTAc
Yes (vs. no) 15.6 33.3 14.3 36.1
Attend PTA meetingsc
Yes (vs. no) 35.5 48.0 36.7 33.7
(continued)
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Oseguera et al. 1145
Analyses
In order to account for the complex survey sampling methodology employed
by NCES, we used the survey set routine in the Stata software, which also
accounts for the clustering of students within schools in the data. Analysis
was divided into two parts to investigate whether or not the preconditions for
the realization of social capital explain the differences in time spent studying
between Southeast Asian, Black, Mexican, and White students. The first part
presents potential to access social capital for the four groups of interest. We
highlight descriptive analyses to create a nuanced understanding of the relationship between the preconditions and our outcome and used analysis of
variance (ANOVA) to test for differences between means across groups. We
used the Brown–Forsythe formula due to unequal sample sizes in this study,
appropriate here because it adjusts the F statistic as it takes into account
unbalanced ANOVA designs and the heterogeneity of the sample variances
(Cohen, 2001). We also conducted Games–Howell (GH) post hoc comparisons to determine how ethnic groups differ from each other across each
measure. In the second part, we explore the contribution of the various
potential sources of social capital on study behavior through ordinary least
squares (OLS) regression models to test the relationships presented in the
descriptive section (see Appendix A for sample description of the variables
Southeast
Asian Black Mexican White
Attend PTA-sponsored meetings
Yes (vs. no) 19.2 28.5 18.5 27.9
Volunteer at the schoolc
Yes (vs. no) 14.8 14.4 12.4 21.4
Mean Parent–School Interaction Indexc
SD 0.4 (0.5) 0.6 (0.5) 0.5 (0.5) 0.6(0.5)
Mean number of child’s friends’ parentsd
SD 1.7 (1.4) 2.6 (1.5) 2.4 (1.5) 3.2 (1.4)
N 167 1,532 1,233 11,568
Note: All variables are measured at the base year. Figures represent percents unless noted.
a. This information comes from the parent questionnaire
b. Item used to create parent-child interaction scale factor score
c. Item used to create summed index of parent–school interaction
d. Variable coded from 0 no parents to 5 five parents.
Table 1. (continued)
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1146 Youth & Society 43(3)
Table 2. Preconditions for Between- and Within-School Sources of Social Capital
Among Southeast Asian, Black, Mexican, and White Students, NELS 1988-1990 Panel
Southeast
Asian Black Mexican White
Opportunities for between-school social capital
School type
Public (vs. private) 90.1 93.2 95.3 88.9
School urbanicity
Urban (vs. suburban/
rural)
53.5 53.7 40.9 20.5
Racial composition
High minority (less
than 25% White)
25.3 37.2 53.3 3.6
Racially mixed
(25%-50% White)
10.8 20.2 15.6 5.6
High White
(50%-75% White)
29.4 22.3 15.8 13.9
Majority White
(76%-90% White)
12.8 11.8 10.9 22.3
Hyper White
(90%-100% White)
21.7 8.6 4.4 54.6
% Receiving reduced lunch
0 14.1 6.8 4.4 12.6
1-10 26.8 21.6 14.8 43.6
11-50 51.9 52.7 51.5 39.1
51-100 7.2 19.0 29.2 4.7
Mean % of 10th
graders who drop
out (SD)
7.8 (7.4) 10.7 (10.8) 13.0 (14.2) 6.0 (8.6)
Mean % of students
going to a 4-year
college (SD)
46.1 (24.9) 40.3 (22.3) 33.0 (20.6) 46.5 (23.4)
Mean % of parents who
volunteer (SD)
13.0 (15.7) 11.3 (15.5) 11.8 (15.8) 12.3 (14.3)
Opportunities for within-school social capital
Academic track
Academic (vs. general) 39.1 33.1 27.1 37.1
Number of friends who have dropped out
None (vs. some, most,
or all)
75.5 67.7 60.5 78.9
(continued)
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Oseguera et al. 1147
in the models). OLS is an appropriate statistical technique here, as our dependent variable is normally distributed. Coefficients represent the difference in
time spent on homework outside of school (in hours) corresponding to a oneunit difference in the independent variable.
In order to evaluate the contribution of the various sources of potential
social capital, analyses were performed in five separate steps. Model 1 highlights the ethnic differences in study behavior. Model 2 controls for the effect
of student background. Models 3 and 4 evaluate the preconditions for familial capital and within- and between-school social capital separately to better
understand the relative contribution of these variables on study behavior, and
Model 5 combines all independent variables into one model.
Multiple imputation was used to account for the common problem of
random missing data on surveys due to item nonresponse (Rubin, 1987).
This method uses information from the sample distributions of the variables
themselves to replace missing values with randomly generated but contextually appropriate values. Our actual procedure used Imputation by Chained
Equations (ICE) in the STATA software. ICE draws imputed values from a
Southeast
Asian Black Mexican White
Among friends, how important is studying
Very important (vs.
somewhat/not
important)
53.9 46.3 37.1 34.4
Teachers push students to achievea
Accurate or very
accurate (vs. somewhat/
not accurate)
80.8 77.6 77.2 80.3
Teaching is good at this school
Agree/strongly agree
(vs. disagree/disagree
strongly)
93.1 83.7 84.8 81.7
Teacher’s expectations
No college 10.7 3.2 3.8 2.6
College 57.0 59.8 55.8 53.9
Teacher doesn’t care 32.3 37.0 40.4 43.5
N 167 1,532 1,233 11,568
Note: All figures are measured at the 10th grade year. Figures represent percentage unless noted otherwise.
a. Item adapted from the school administrator questionnaire.
Table 2. (continued)
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1148 Youth & Society 43(3)
posterior distribution, using OLS regression models to replace missing values for continuous variables, and logit models to replace missing values for
binary or ordinal variables (Royston, 2004). Thus, we generated five subsidiary data sets, each with different randomly imputed values for both individual- and school-level data. Our hypothesized regression models were then
fitted separately in each of the imputed datasets, and the results were averaged and corrected for the inclusion of the random variation in each of the
imputed datasets. Since the imputed data sets themselves have no missing
values except for the dependent variable that was not imputed, sample size
was preserved (see Appendix B that lists the actual number of missing cases
that were imputed).
Results
The mean number of hours per week spent on homework outside of school
for Southeast Asian students is 7.1 hr (SD 4.9), followed by White students at 5.5 hr (SD 4.3), Mexican students at 5.0 hr (SD 4.0), and
Black students at 4.9 hr (SD 3.8). The difference between Southeast
Asian students and the other ethnic groups is statistically significant:
F(3, 13942) 40.718, p .001. In other words, Southeast Asian students
report doing an hour and a half more homework outside of school than
their White peers and just over 2 hr more than their Black and Mexican
counterparts.
Descriptive Results of the Preconditions
for the Realization of Familial Capital
We included several measures of potential familial capital to tap a variety of
dimensions of the concept and better understand differences in study behavior beyond cultural explanations. As stated earlier, social capital’s influence
is in its conversion. Although we did not evaluate social capital in the absolute sense, we did evaluate the preconditions or proxies of social capital that,
utilized effectively, can result in social capital realization. The first of these
was the frequency of interactions between parents and children. Using this
measure, we found that less than half of Southeast Asian parents report frequent discussions about school experiences with children, compared to two
thirds of Mexican parents and more than three fourths of Black and White
parents (see Table 1). Similarly, Southeast Asian parents are least likely
among the four ethnic groups to report regular discussions about high school
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Oseguera et al. 1149
or post–high school plans with their children. Thus, results are not surprising
when these measures are combined in a summary index. The mean for nonSoutheast Asian parents is significantly higher than for Southeast Asian
parents: F(3, 14496) 50.413, p .001.
In our analyses, the majority of Southeast Asian, Mexican, and White children reside in two parent families. However, Black children are significantly
less likely to reside with both parents (60% of Black families are headed by
one parent compared to approximately 30% among each of the other three
groups).8
Relationships that result in advantageous opportunities for familial
social capital realization can also be measured by family–school interactions. In all measures, Southeast Asian parents are somewhat less likely
than Mexican parents and significantly less likely than their Black or
White peers to participate in school events. If one is comparing potential
social capital advantages between groups, it appears that both Southeast
Asian and Mexicans fall short. Their rate of PTA membership, attending
PTA sponsored activities, and volunteering at school is nearly half the rate
of the White and Black families. When all measures are combined in a
single index (see Table 1), Southeast Asian parents achieve the lowest
mean score (0.40), followed by Mexican parents (0.50), with the highest
mean among Black and White parents (0.60).9
Stated another way, 40% of
Southeast Asian parents performed at least one of the involvement activities at school compared to 50% of Mexican parents and 60% of Black and
White parents, respectively.10 In addition, Southeast Asian parents know
1.7 of their child’s friends’ parents, whereas Mexican, Black, and White
parents know 2.4, 2.6, and 3.2 of the parents, respectively. These differences in means are statistically significant: F(3, 14496) 44.23, p .001.
From this measure, it appears that Mexican, Black, and White children
may be more likely than Southeast Asian children to benefit from social
closure in the school community.11
By most measures, Southeast Asian students have access to fewer preconditions for the realization of familial social capital than do Mexican,
Black, and White students, when these opportunities are measured as the
frequency of interactions between parents and children, parents and schools,
and parents and other children’s parents. The exception is that Southeast
Asian parents tend to have higher educational expectations of their children
than do other parents in this study.12 The relative influence of these higher
expectations on the study habits of children is presented later in the multivariate analyses.
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1150 Youth & Society 43(3)
Descriptive Results of Between-School
Preconditions for the Realization of Social Capital
We begin by exploring the various school contexts of the four ethnic groups.
Overall, Southeast Asian and White students attend schools with a higher
SES population than Mexican or Black students. For example, only 7% of
Southeast Asian and 5% of White students in the sample attend schools in
which, on average, more than 50% of students receive reduced lunch,
whereas Mexican and Black students are significantly more likely to be concentrated in schools where more than 50% of students receive reduced lunch:
F(3, 14496) 270.136, p .001. Mexican and Black students also attend
schools with higher drop-out rates, F(3, 14496) 412.48, p .001, and fewer
college bound students, F(3, 14496) 175.433, p .001. There are no differences, however, in the likelihood of parents being more involved in the
schools these students attend. In fact, all the students in this sample attend
schools where less than 15% of parents volunteer.
The final school context13 variable presented is the racial composition of
the school. We find that the Mexican and Black students in this sample are
significantly more likely to attend schools with higher concentrations of lowincome minority students. Conversely, White and Southeast Asian students
are more likely to attend a school where White students are the majority,
F(3,14496) 2215.95, p .001. Overall, the between-school preconditions
for the realization of social capital portrait shows more favorable school conditions for the Southeast Asian and White students than their Black and
Mexican counterparts, a finding further explored in the multivariate analyses.
Descriptive Results of Within-School
Preconditions for the Realization of Social Capital
Next, we turn to potential opportunities for social capital activation found
within schools. Table 2 shows large ethnic differences in peer group norms
and behaviors. Southeast Asian students have fewer friends who drop out of
school and more friends who consider studying important than do Mexican
and Black students. Furthermore, 76% of Southeast Asians report having no
friends who dropped out of high school, whereas only 68% of Black students
and 61% of Mexican students report having no friends drop out of high
school, F(3,14496) 88.48, p .001.14 On the other hand, nearly 55% of
Southeast Asian students report that studying is very important to their
friends compared to 46% of Black students, 37% of Mexican students, and
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Oseguera et al. 1151
34% of White students, F(3, 14496) 13.255, p .001.15 These results are
consistent with the findings of Steinberg et al. (1996), who reported that
Asian American students’ peers are more likely to encourage their academic
success than the peers of other groups.16
Another within-school precondition for the realization of social capital we
explore is the relationship between students and teachers. Close to 60% of all
students in the sample report that teachers expect them to graduate from college (see Table 2). However, there are larger ethnic differences between students who report that their teachers do not care about their post–high school
plans. Close to or upwards of 40% of Black, Mexican, and White students
report that teachers do not care about their post–high school plans, compared
to less than one third of Southeast Asians. When school administrators were
asked whether teachers motivate their students to achieve in school, administrator agreement rate was highest in the schools attended by Southeast Asians.
Students’ motivation to perform well is lessened when they do not feel that
teachers care about their performance.
The final measure we evaluate is academic track placement in high school.
Southeast Asians are most likely to be enrolled in the academic track (39%),
followed closely by White students (37%) in comparison to their Black and
Mexican peers (33% and 27%, respectively). Higher-track placement, along
with other within-school preconditions for the realization of social capital
findings, can help explain why Southeast Asian students in this sample report
longer hours spent on homework outside of school.
Multivariate Results of Familial and Within- and
Between-School Preconditions for the Realization
of Social Capital as Reflected on Study Habits
We fit five multivariate models to test whether differences in potential opportunities for the realization of social capital relate to variation in study habits
across the ethnic groups. Table 3 presents all five of our fitted regression models with time spent on homework outside of school per week as the dependent variable.17 We first highlight the R2
change to examine how much variation
in time spent studying is accounted for by preconditions for social capital
realization.
Model 1 only includes the ethnic groups, whereas Model 2 adds background characteristics. With the addition of familial preconditions for the
realization of social capital variables (Model 3), the R2
increases slightly
from .061 to .081. The largest increase occurs in Model 4, where familial
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1152 Youth & Society 43(3)
Table 3. Coefficients From Ordinary Least Squares Models Predicting the
Hours Students Spend on Homework Outside of School; NELS 1988-1990 Panel
(N 13,946)
Model 1
Coef.
Model 2
Coef.
Model 3
Coef.
Model 4
Coef.
Model 5
Coef.
Constant 7.149*** 6.453*** 3.905*** 5.466*** 3.855***
Race (Southeast Asian excluded)
Black 2.249*** 2.408*** 2.501*** 2.313*** 2.314***
Mexican 2.131*** 2.347*** 2.363*** 1.904*** 1.915***
White 1.648*** 1.733*** 1.774** 1.423** 1.440**
Background characteristics
Immigration generation
(Third gen excluded)
First generation 0.427 0.340 0.227 0.179
Second generation 0.441 0.360 0.281 0.228
Primary Language:
English (Non-English
dominant excluded)
0.725 0.761 ** 0.784 ** 0.818 **
SES 1.212*** 0.827 *** 0.703 *** 0.519 ***
Female 1.108*** 1.024 *** 0.869 *** 0.829 ***
Preconditions for familial social capital
Family composition
(single parent
excluded)
Two parent 0.333** 0.297 *
Parent–School
Interaction Index
0.183 0.029
Parent–Child
Interaction Index
0.161** 0.079
Closure 0.063 0.027
Parents’ educational expectations for child (HS grad or less high school excluded)
Two-year vocational/
technical college
0.385 0.300
Attend 4-year college 1.481*** 1.140**
Graduate 4-year
college
1.686 *** 1.154**
Preconditions for between school social capital
% Receiving reduced
lunch
0.223* 0.233*
% of 10th graders who
drop out
0.001 0.000
(continued)
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Oseguera et al. 1153
capital variables are omitted and within- and between-school precondition
variables are introduced (the R2
increases from .061 to .120). When familial
preconditions for social capital are reintroduced in Model 5 (i.e., the final
Model 1
Coef.
Model 2
Coef.
Model 3
Coef.
Model 4
Coef.
Model 5
Coef.
% of students going to
4-year colleges
0.003 0.003
% of parents who
volunteer
0.001 0.002
School type (Private
excluded)
Catholic 0.294 0.401
Public 0.769 0.739
Percent White (Mixed
White excluded)
Hyper White 0.198 0.157
Majority White 0.043 0.022
High White 0.025 0.017
High minority 0.291 0.310
Preconditions for within school social capital
High school program (academic excluded)
General track 0.905*** 0.796***
Friends who have dropped out (Some/most excluded)
None 0.570*** 0.454***
Importance of studying to friends (Not at all excluded)
Somewhat 1.224*** 1.163***
Very 2.184*** 2.110***
Teachers’ expectations (College excluded)
No college 0.329** 0.199
Doesn’t care 0.242 0.154
Teachers push students to achieve (Not accurate/somewhat accurate excluded)
Accurate/very
accurate
0.094 0.089
Perception that teaching is good (Disagree/strongly disagree excluded)
Agree/strongly agree 0.515*** 0.506***
R-squared 0.004 0.061 0.081 0.120 0.128
***p .001. **p .01. *p .05. +
p .10
Table 3. (continued)
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1154 Youth & Society 43(3)
fitted model), the R2
increases slightly to .128. Thus, between- and withinschool preconditions help explain studying hour differences more than familial preconditions.18
After accounting for all variables in the model, we find that study time
differences between Southeast Asian and other ethnic groups in the sample
are reduced. With all other predictors being equal, Southeast Asian students,
on average, spend about 3.9 hr on homework outside of school, compared to
Whites (2.5 hr), Mexicans (2 hr), and Blacks (1.6 hr). Stated another way,
after controlling for both familial and within- and between-school preconditions, Southeast Asian students are predicted to do 2.3 more hr of outside
homework per week than Black students, 1.9 more hr than Mexican students
and only 1.4 more hr than White students.
Once within- and between-school preconditions are introduced, the female–
male difference is also reduced. That is, women only do 0.83 more hr of
homework outside of school than men. We see similar results when introducing SES. Students from higher SES levels do 0.52 more hr of homework
outside of school than lower SES students. Also, on average, students who
come from two parent families do 0.30 more hr of homework outside of
school than those who come from single-parent families.
It appears that between-school context variables have fewer significant
effects on the variation in hours spent on homework outside of school among
Southeast Asian, Black, Mexican, and White students than expected, although
parameter estimates reveal that higher proportions of students receiving free
or reduced lunch within a school are linked to less time spent on homework
for students in that school.
On the other hand, comparison of data taken from the within-school
environment shows that relationships within schools may be strongly
related to students’ study behavior. With the addition of within-school
preconditions for social capital measures, differences between Southeast
Asian and other groups are reduced even more so than in the model with
only familial preconditions for social capital (see Table 3). Academic track
placement is linked to more hours spent on homework outside of school.
Placement in a general track is associated with an average of 0.80 less hr
spent on homework compared to students in the college preparatory track.
Peer relationships, in terms of having no friends who drop out of high
school and maintaining friendships in which peers value studying, are also
linked to more homework outside of school. Reporting that the teaching is
good at one’s school is also related to spending more hours on homework
outside of school. Finally, teachers’ expectations are also linked to the
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Oseguera et al. 1155
homework effort. Students who report that teachers do not expect them to
attend college do .20 less hr of homework than students who report that
teachers expect them to go to college.
The separate models show that parents appear to have some influence on the study behavior of Southeast Asian, Black, Mexican, and
White students, but so too do peers and teachers. Unlike studies that focus
on differences in access to between school nonfamilial social capital
(Stanton-Salazar & Dornbusch, 1995), our research highlights the importance of relationships within schools and suggests that these preconditions for the eventual realization of social capital help explain study
behavior differences between groups more than any cultural explanation
offered in the past.
Discussion and Conclusion
This article explores preconditions necessary to forge interconnected relationships that influence positive study habits and eventual school success.
Although it does not test social capital or its conversion, it does develop a
more comprehensive understanding of academic achievement by exploring alternative preconditions for the potential activation of social capital.
It specifically presents a conceptual contribution by verifying how we
must first consider the preconditions for the potential activation of social
capital, as understanding these opportunities clearly helps explain academic achievement among Southeast Asian, Black, Mexican, and White
high school youth.
The main goal of this research is to investigate the extent to which different preconditions for social capital explain variation in students’ study habits.
Although academic literature and popular media have argued that families
are largely responsible for differences between race and ethnic groups, our
research shows that relationships outside the family play a highly significant
role in explaining variations.
We do not suggest that families have no influence on children’s study
habits. Rather, we demonstrate how typical measures using mostly familial
preconditions for social capital cannot entirely explain the difference between
the educational behaviors of Southeast Asian, Black, Mexican, and White
students. Our results suggest that familial social capital does not account for
all ethnic group differences in study habits.
We do, however, acknowledge that familial influence on children’s
study habits may operate through channels other than those we typically
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1156 Youth & Society 43(3)
characterize as social capital. In fact, conceptualizations and measures of
familial capital may have to be adapted to fit the varied situations and
experiences of diverse minority ethnic groups in order to be usefully
applied to those communities. We cannot assume that familial social capital has the same effects on the educational outcomes of children of all
ethnic backgrounds. Minority and immigrant children may rely on familial capital less than White and native-born children, as illustrated by the
Southeast Asian students in this sample who report less opportunity for
familial capital, yet high levels of achievement. Perhaps there are measures of familial social capital that would better capture the ways in
which minority and recently immigrated families shape their children’s
achievements.
In this research, we demonstrate that between- and within-school preconditions for social capital realization play a critical role in explaining
students’ studying behavior, specifically, ethnic differences in studying
time outside of school. Since study behavior can be viewed as a proxy for
achievement, these between- and within-school measures further help
inform our knowledge of why certain groups achieve greater academic success in the classroom.
Our findings suggest that the potential acquisition and opportunities for
social capital may vary by race, ethnicity, and gender. Ethnicity appears to be
particularly important in influencing the resources that students obtain from
nonfamily relationships. Gender is also important to consider, as the girls in
this sample are somewhat more likely to study than boys. A deeper understanding of why girls spend more time studying is warranted, especially as
women are now graduating from high school, enrolling in college, and completing college at higher rates than men (Astin & Oseguera, 2005; Oseguera,
2006; Rumberger & Lim, 2008). In essence, more work is needed to see how
the sources of social capital, and resources gained from them, differ according to race, ethnicity, and gender.
Our results suggest some directions for future research. An issue that we
do not address empirically is the activation of social capital. Lareau and
Horvat (1999) contend that in order to gain resources from a source of social
capital students must be able to use it in specific environments. Students’
capacity to use their social capital may be circumscribed by their race or ethnicity and the race or ethnicity of those who hold resources. For example,
Lareau and Horvat show that African American parents attempting to participate in their child’s school may be prevented from doing so by teachers’
perceptions that such parents are “pushy.” Thus, possibly the social capital
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Oseguera et al. 1157
brought to school by Black and Mexican students is not activated as much as
that of Southeast Asian students. Perhaps the interventions of Mexican and
Black extended family members are not valued because these advocates are
not parents and thus not perceived as the proper guardians with whom information should be shared. In contrast, the mannerisms that Southeast Asian
parents bring to their interactions with teachers may win teachers’ approval,
as they are said to treat teachers with great respect based on their Confucian
heritage (Nash, 1987). Teachers may respond well to this treatment and share
more information and support with this group. In other words, perceptions of
the ethnic groups may affect the extent to which they are able to actualize the
social capital they receive from their families. In sum, much more research is
needed on how students are able to activate their social capital in various
in-school and out-of-school settings.
Our challenge is to push those exploring social capital to think about
how race and ethnicity influence its acquisition and expression. Research
done on the effects of social capital using predominantly White samples has
led to generalizations among policy makers and the public regarding appropriate steps to enhance academic success. Most of the research done on
social capital and educational achievement has focused on the role of the
family. However, our results suggest that, in terms of explaining ethnic
group differences in study habits, intangible resources gained from families
may not be as important as those gained from relationships within schools.
These results suggest that educators should concentrate their efforts on
equalizing access to such relationships by designing policies to reduce ethnic segregation among peers and encourage teachers to mentor students of
all ethnic groups.
Finally, before we can truly understand how family and nonfamily practices influence school success, we must investigate their influence on all
social groups—immigrants, minorities, and low-SES students. It is not selfevident that what works for the majority, usually middle-class Whites, will
also work for others. Social capital, in this case, ultimately refers to the useful
though intangible resources students can use to enable their educational success. To provide a more complete understanding of inequality in schools, we
must explore the preconditions for the potential activation of social capital in
distinct contexts, how these intangible resources are distributed, and, finally,
how they are eventually realized. This holistic research approach will provide
policy makers and practitioners with the knowledge necessary to minimize
educational inequality and maximize the educational achievement of all
students.
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1158 Youth & Society 43(3)
Appendix A
Descriptive Statistics of the Variables that Were Used
in the Analyses
Variable M
SD (of
continuous
variables) Minimum Maximum
Dependent variable
Hours per week spent on
homework outside of school
(N 13, 946)
5.404 4.245 0 18
Independent variables
Race
Southeast Asian 0.010 0 1
White 0.800 0 1
Mexican 0.060 0 1
Black 0.130 0 1
Immigration generation
First generation 0.040 0 1
Second generation 0.050 0 1
Third generation 0.900 0 1
Primary language: English 0.940 0 1
SESa 0.035 0.739 2.97 2.56
Gender: Female 0.500 0 1
Family composition
Two parent (versus single parent) 0.670 0 1
Parent–School Interaction
Index
0.560 0 1
Parent–Child Interaction
Indexb
4.221 0.902 0 5
Closurec 3.050 1.474 0 5
Parents’ educations expectations for child
HS grad or less than high
school
0.070 0 1
Two-year vocational/technical
college
0.140 0 1
Attend 4-year college 0.100 0 1
Graduate 4-year college 0.700 0 1
% receiving reduced lunchd 1.470 0.799 0 3
% of 10th graders who drop
out
7.110 9.630 0 100
(continued)
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Oseguera et al. 1159
Variable M
SD (of
continuous
variables) Minimum Maximum
% of students going to 4-year
colleges
44.830 23.367 0 100
% of parents who volunteer 12.110 14.591 0 100
School type
Private 0.040 0 1
Catholic 0.060 0 1
Public 0.900 0 1
Percent White
Hyper White 0.450 0 1
Majority White 0.200 0 1
High White 0.150 0 1
Mixed White 0.080 0 1
High minority 0.110 0 1
High school program
General track 0.640 0 1
Friends who have dropped out
Some/most 0.240 0 1
None 0.760 0 1
Importance of studying to
friends
Not at all 0.090 0 1
Somewhat 0.550 0 1
Very 0.360 0 1
Teachers’ expectations
College 0.550 0 1
No college 0.430 0 1
Doesn’t care 0.020 0 1
Teachers push students to achieve
Accurate/very accurate 0.800 0 1
Perception that teaching
is good
Agree/strongly agree 0.820 0 1
N 14,500
a. Continuous variable from –3 to 3
b. Scaled score 0 not regularly to 5 regularly
c. 0 no parents to 5 five parents.
d. 0 0% to 3 51-100%.
Appendix A. (continued)
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1160 Youth & Society 43(3)
Appendix B
Descriptives of Variables With Missing Cases
That Were Imputed
Variable Actual Missing Missing %
Dependent variable
Hours per week spent on
homework outside of school
(N 13, 946)
13,946 554 3.8
Independent variables
Immigration generation 13,515 985 6.8
Primary language: English 14,474 26 0.2
Family composition 14,352 148 1.0
Parent–School Interaction Index 13,294 1,206 8.3
Parent–Child Interaction Index 13,487 1,013 7.0
Closure 12,218 2,282 15.7
Parents’ expectations 13,039 1,461 10.1
% Receiving reduced lunch 12,896 1,604 11.1
% of 10th graders who drop out 13,127 1,373 9.5
% of students going to 4-year
colleges
11,697 2,803 19.3
% of parents who volunteer 11,633 2,867 19.8
School type 14,442 58 0.4
Percent White 13,422 1,078 7.4
High school program 13,987 513 3.5
Friends who have dropped out 13,637 863 6.0
Importance of studying to friends 13,581 919 6.3
Teachers’ expectations 13,735 765 5.3
Two parent (versus single parent) 11,864 2,636 18.2
Perception that teaching is good 13,890 610 4.2
N 14,500
Note. Only variables in the analyses with missing data are included in this table.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the authorship
and/or publication of this article.
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Oseguera et al. 1161
Funding
Support for this research was provided by a junior faculty fellowship grant from the
University of California All Campus Consortium on Research for Diversity (UC
ACCORD).
Notes
1. For important exceptions see Conchas (2001, 2006), Goyette and Conchas
(2002), Stanton-Salazar and Dornbusch (1995), and Zhou and Bankston (1998).
2. Because the Vietnamese sample in the NELS is small, we decided to aggregate
the entire Southeast Asian sample to make meaningful analytic comparisons
with the other three ethnic groups.
3. 0 no hours, 3 1-3 hr, 6 4-6 hr, 9 7-9 hr, 12 10-12 hr, 15 13-15 hr,
18 over 15 hr per week performing homework outside of school.
4. This is consistent with the work of Teachman, Paasch, and Carver (1996, 1997).
5. These measures are found in other social capital research (Teachman et al., 1996,
1997).
6. For this measure, a lower percentage implies greater opportunity for social capital realization.
7. For this measure, a lower percentage implies greater opportunity for social capital realization.
8. McLanahan and Sandefur (1994) noted that children living in single-parent families have access to less social capital because they lack the information, support,
and supervision of the absent parent.
9. These differences in means are statistically significant, F(3, 14496) 43.3,
p .001.
10. This may speak to the unfamiliarity of the school system among the two more
recently immigrated groups, also noted by other researchers (Lareau & Horvat,
1999; Valenzuela, 1999).
11. Another possible interpretation is that Southeast Asian students have fewer
friends than do the other 3 racial/ethnic groups in this study. We contend, though,
that the variable still measures community involvement, as students who have
few friends are less likely to be involved in closely knit, supportive networks of
relationships.
12. In her article on immigrant groups in the U.S., Feliciano (2006b) writes that
higher group premigration educational status encourages higher parental aspirations in the U.S. context, which subsequently shapes the educational expectations of the second generation youth.
13. We also explored school size as a school context variable, but it did not show an
effect on study habits in either the descriptive results or the multivariate models.
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1162 Youth & Society 43(3)
14. A Games–Howell post hoc test indicated that though the differences between
the means of Mexicans, Southeast Asian, Whites, and Blacks were statistically
significant (p .01), the differences between Whites and Southeast Asian were
not (p ! .05).
15. Games–Howell post hoc test indicated that, with the exception of Mexicans and
Whites, the differences in means were statistically significant for the other racial
groups (p .01).
16. There are several problems with using the reported values and behaviors of
friends as a proxy for the social capital available from these sources. The biggest
difficulty with this measure is that students select their friends. It is difficult to
know the extent to which observed coefficients in multivariate models are due
to the influence of friends and the extent to which they are due to the student’s
own unobserved characteristics. Studious students tend to choose those with like
norms and behaviors as friends.
17. We also fit similar models with the dependent variable as logged number of
hours spent on homework outside of school. The results from these models are
available from the authors upon request. Since the results were similar, here we
simply report coefficients for the linear model using hours spent on homework
as the dependent variable for ease of interpretation.
18. For brevity, only the final model is discussed in detail.
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Bios
Leticia Oseguera is an assistant professor in the Department of Education Policy
Studies at the Pennsylvania State University. She received her PhD in higher education and organizational change from UCLA. Her research focuses on the stratification
of American higher education, the civic role of higher education, college transitions,
and baccalaureate degree attainment for underrepresented groups.
Gilberto Q. Conchas is associate professor and chancellor’s fellow at the University
of California, Irvine. He received a PhD in sociology from the University of Michigan,
Ann Arbor. He is the author of The Color of Success and Small Schools and Urban
Youth.
Eduardo Mosqueda is an assistant professor of education at the University of
California, Santa Cruz. His research focuses on how school context factors such as
academic tracking and the segregation of low-income students of color affect the
mathematics achievement of English learners (ELs). He recently completed his doctoral studies at the Harvard Graduate School of Education where he was awarded the
Spencer Dissertation Fellowship. He has also taught both middle and high school
mathematics.
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