Abstract
In 1960, over 60 % of bachelor degrees were awarded to men. However, the rate of women’s college completion has steadily risen and, by 2004, women received nearly 60 % of bachelor degrees. Drawing on the theoretical contributions of James Coleman, this paper examines the ability of social capital to explain observed differences in college enrollment. We use data from the 2002 Educational Longitudinal Study to examine social capital and quantify the strength of its relationship to college enrollment. We establish that men are currently disadvantaged with respect to key social capital variables, consistent with other published studies. We use logistic regression modeling to show that, after controlling for relevant variables, social capital is indeed related to college enrollment, and we provide an estimate of the degree to which the gender difference in enrollment can be explained by differences in social capital. In particular, we show that social capital reduces the odds ratio of women enrolling in college compared to men from 1.63 to 1.41. We show also that when grade point average is added to social capital, the odds ratio reduces from 1.41 to 1.23, showing that a substantial amount, but not all, of the gender disparity in college enrollment can be explained by these factors. In our final model, we test whether gender significantly interacts with social capital on college enrollment, a finding that would be consistent with women receiving differential returns to social capital. We find that women do not receive differential returns to social capital in comparison with men.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Steelman et al. (2002) have argued that more recent studies of the relationship between sibship size and educational outcomes that have utilized improved methodology suggest that it may be time to revise the widely accepted findings about this relationship. These studies, which utilize longitudinal change models, find that an increase of sibship size has negligible effects on academic tests of verbal ability and possibly a positive effect on math test performance. At the same time, Steelman et al. (2002) noted that these newer studies have their own methodological shortcomings and that their outcomes have yet to be corroborated by a critical mass of scholarship (Steelman et al. 2002).
We have conceptualized parent involvement broadly to include involvement that is not necessarily academic in nature (i.e. involvement in structured activities, likely to benefit boys over girls due to their greater involvement in team sports).
Of the 17.8 million undergraduate students who were enrolled in postsecondary education in the fall 2012, 40 % were enrolled in 2-year community colleges.
At the scale level, there were still individuals, who by virtue of not having responded to a majority of items on a scale, had a missing value for that scale. According to Gottschall et al. (2012), given incomplete questionnaire data, a researcher “can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale scores” (pp. 22–23). Like Gershoff et al. (2007), we used a combination of the two approaches in this paper. In addition to the person mean imputation at the item-level, we used multiple imputation at the scale level as described in greater detail later in the paper.
Given that individuals are often known to seek out friends who share their college aspirations, the variable, Perceived Importance of Friends to Achieve, may be endogenous. Because current research suggests that the norms and values of a particular peer group significantly impact the benefits that may be accrued from increased levels of social capital, we include these items in our analysis, limiting our conclusions regarding descriptive claims about their contribution to explaining college enrollment variance.
The principle of imputation is that the increased uncertainty due to imputation is more than offset by the increased sample available for inclusion in the multivariate analysis (i.e., a logistic regression in this case).
None of the inter-correlations between scales exceeded 0.51, indicating that multicollinearity would not be an issue for our regression analyses.
Please see footnote 2.
We consider the model controlling for demographic variables to be a baseline model because demographics should be independent of gender since parents of all backgrounds have essentially the same chance of having a boy or girl. Therefore, demographic controls should simply improve the precision of the estimates without modifying them.
According to Breen et al. (2013), in linear models, the total relationship of a predictor on an outcome variable may be decomposed into a direct and mediated (indirect) effect. In logit models, however, total effects cannot be decomposed in a similar way. In particular, “[g]iven a dichotomous outcome variable, y, the logit coefficient for x omitting the control variable, z, will not equal the sum of the direct and indirect (via z) effects of x on y” (p. 165).
By focusing on the females, conceptually our analysis is analogous to estimating an average treatment effect on the treated (ATT). Were we to conduct the analysis on all individuals in the sample, our analysis conceptually would be analogous to estimating a sample average treatment effect (SATE) for all individuals. Likewise, conducting the analysis among males would be analogous to estimating an average treatment on the controls (ATC). We say it is conceptually analogous, because our focus in this study is on making descriptive rather than causal claims.
To clarify our procedure, we use the usual hypothesis test associated with the logistic model and use the differential log-odds estimator to obtain a point estimate that gets around the problem of interpreting nested logistic regression coefficients (as pointed out by Breen et al. 2013; Freedman 2008). This point estimator allows us to estimate the magnitude of the relation of our social capital and demographic variables with the female advantage in college enrollment in terms of log odds.
Because of the nature of the ELS data set, in which individual survey respondents are sampled from within schools, contextual school level factors may be important for predicting college enrollment, in addition to individual level characteristics. To test this out, a multilevel analysis (HLM) was run that takes into account the nature of the school level data nested within schools. We did not expect to observe a substantive difference resulting from this new analysis given that in our original analysis the intraclass correlation coefficient (ICC), a measure of the between school variance of college enrollment relative to the total college enrollment variance, was small. Not only does a small ICC suggest a small design effect due to nesting, but our use of STATA’s mi svy command in our logistic regression analyses, allowed our standard errors to be cluster robust. As expected, therefore, our substantive findings from the HLM analyses were identical with those from the logistic regression analyses.
Although focused on gender and the extent to which social capital as a main effect or as a two-way interaction with gender reduces the likelihood of girls’ college enrollment relative to boys’, in acknowledgement of a literature that suggests an interaction between social capital and other aspects of cultural capital (specifically, ses and race/ethnicity) on college enrollment, we carried out additional analyses to test whether these two-way interactions are statistically significant based on our data. The results of these additional analyses, given in the Appendix, suggest that neither set of two-way interactions with social capital is statistically significant. For the two-way interaction between race/ethnicity and social capital on college enrollment we obtain F(60, 248.1) = 1.14, p = 0.251; and for the two-way interaction between ses and social capital on college enrollment, we obtain F(15, 205.4) = 1.51, p = 0.103.
References
Allison, P.D. (1999). Multiple imputation for missing data: A cautionary tale. http://www.ssc.upenn.edu/~allison/MultInt99.pdf.
American Association of Community Colleges. (2014). 2014 Fact Sheet. Washington, DC: Author.
American Association of University Women. (2012). Graduating to a pay gap: The earnings of men and women one year after college graduation. Washington, DC: Corbett, C. & Hill, C.
American Council on Education. (2006). Gender equity in higher education. Washington, DC: Jacqueline E. King.
Arum, R., Gamoran, A., & Shavit, Y. (2007). Inclusion and diversion in higher education: A study of expansion and stratification in 15 countries. In R. Arum, A. Gamoran, & Y. Shavit (Eds.), Stratification in higher education: A comparative study (pp. 1–35). Palo Alto, CA: Stanford University Press.
Astone, N. M., & McLanahan, S. (1991). Family structure, parental practices and high school completion. American Sociological Review, 56(3), 309–320.
Blossfeld, H., & Shavit, Y. (1993). Persisting barriers: Changes in educational opportunity in thirteen countries. In H. Blossfeld & Y. Shavit (Eds.), Persistent inequality: Educational attainment in thirteen countries. Boulder, CO: Westview Press.
Breen, R., Karlson, K., & Holm, A. (2013). Total, direct, and indirect effects in logit and probit models. Sociological Methods and Research, 42(2), 164–191.
Brookhart, S. M. (1993). Teachers grading practices: Meaning and values. Journal of Educational Measurement, 30(2), 123–142.
Buchmann, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71(4), 515–541.
Buchmann, C., DiPrete, T. A., & McDaniel, A. (2008). Gender inequalities in education. Annual Review of Sociology, 34(1), 319–337.
Budig, M., & England, P. (2001). The wage penalty for motherhood. American Sociolocial Review, 66(2), 204–225.
Carbonaro, W. J. (1998). A little help from my friend’s parents: Intergenerational closure and educational outcomes. Sociology of Education, 71(4), 295–313.
Carbonaro, W. J. (1999). Opening the debate on closure and schooling outcomes: Comment on Morgan and Sørensen. American Sociological Review, 64(5), 682–686.
Carter, R. S., & Wojtkiewicz, R. A. (2000). Parental involvement with adolescents’ education: Do daughters or sons get more help? Adolescence, 35(107), 29–44.
Cohen, J. (1998). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.
Coleman, J. (1987). Public and private high school: The impact of communities. New York: Basic Books.
Coleman, J. S. (1988). Social capital in the creation of human capital. The American Journal of Sociology, 94(Supplement: Organizations and Institutions: Sociological and Economic Approaches to the Analysis of Social Structure), S95–S120.
Cornwell, C., Mustard, D. B., & Van Parys, J. (2013). Noncognitive skills and the gender disparities in test scores and teacher assessments. Journal of Human Resources., 48(1), 236–264.
Dika, S. L., & Singh, K. (2002). Applications of social capital in educational literature: A critical synthesis. Review of Educational Research, 72(1), 31–60.
DiPrete, T. A., & Buchmann, C. (2006). Gender-specific trends in the value of education and the emerging gender gap in college completion. Demography, 43(1), 1–24.
DiPrete, T. A., & Buchmann, C. (2013). The rise of women: The growing gender gap in education and what it means for American schools. New York: Russell Sage Foundation.
DiPrete, T. A., & Jennings, J. (2012). Social and behavioral skills and the gender gap in early educational achievement. Social Science Research, 41(1), 1–15.
Downey, D. B. (1995). When bigger is not better: Family size, parental resources, and children’s educational performance. American Sociological Review, 60(5), 746–761.
Engberg, M., & Wolniak, G. (2010). Examining the effects of high school contexts on postsecondary enrollment. Research in Higher Education, 51(2), 132.
Entwisle, D. R., Alexander, K., & Olson, L. S. (1994). The gender gap in math: Its possible origins in neighborhood effects. American Sociological Review, 59(6), 822–838.
Farkas, G., Grobe, R. P., Sheehan, D., & Shuan, Y. (1990). Cultural resources and school success: Gender, ethnicity, and poverty groups within an urban school district. American Sociological Review, 55(1), 127–142.
Frank, K. A., Muller, C., Schiller, K. S., Riegle-Crumb, C., Mueller, A. S., Crosnoe, R., & Pearson, J. (2008). The social dynamics of mathematics coursetaking in high school. American Journal of Sociology, 113(6), 1645–1696.
Freedman, D. A. (2008). Randomization does not justify logistic regression. Statistical Science, 23, 237–249.
Gershoff, E. T., Aber, J. L., Raver, C. C., & Lennon, M. C. (2007). Income is not enough: Incorporating material hardship into models of income associations with parenting and child development. Child Development, 78(1), 70–95.
Giordano, P. C. (2003). Relationships in adolescence. Annual Review of Sociology, 29, 257–281.
Glazer-Raymo, J. (2008). Unfinished agendas: New and continuing gender challenges in higher education. Baltimore, MD: Johns Hopkins University Press.
Goldin, C. (2006). The quiet revolution that transformed women’s employment, education, and family. American Economic Review, 96(2), 1–21.
Gottschall, A. C., West, S. G., & Enders, C. K. (2012). A comparison of item-level and scale-level multiple imputation for questionnaire batteries. Multivariate Behavioral Research, 47(1), 1–25.
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576.
Hallinan, M. T. (2008). Teacher influences on students’ attachment to school. Sociology of Education, 81(3), 271–283.
Hallinan, M. T., & Kubitschek, W. N. (1999). Conceptualizing and measuring school social networks: Comment on Morgan and Sørensen. American Sociological Review, 64(5), 687–693.
Haynie, D. L. (2001). Delinquent peers revisited: Does network structure matter? American Journal of Sociology, 106(4), 1013–1057.
Hughes, J. N., Cavell, T. A., & Wilson, V. (2001). Further support for the developmental significance of the quality of the teacher-student relationship. Journal of School Psychology, 39(4), 289–301.
Jacob, B. (2002). Where the boys aren’t: Non-gognitive skills, returns to school and the gender gap in higher education. Economics of Education Review, 21, 589–598.
Jennings, W. G., Gover, A. R., & Pudrzynska, D. (2007). Are institutions of higher learning safe? A descriptive study of campus safety issues and self-reported campus victimization among male and female college students. Journal of Criminal Justice Education, 18(2), 191–208.
Kelley, S. (2008). What types of students’ effort are rewarded with high marks? Sociology of Education, 81(1), 32–52.
Kim, D. H., & Schneider, B. (2005). Social capital in action: Alignment of parental support in adolescents’ transition to postsecondary education. Social Forces, 84(2), 1181–1206.
Koerner, B. (1999, February). Where the boys aren’t. U.S. News and World Report, pp. 47–55.
Krein, S., & Beller, A. (1988). Educational attainment of children from single-parent families: Differences by exposure, gender, and race. Demography, 25, 221–234.
Lange, M., Dronckers, J., & Wolbers, M. H. (2014). Single-parent family forms and children’s educational performance in a comparative perspective: Effects of school’s share of single-parent families. School Effectiveness and School Improvement, 25(3), 329–350.
Lin, N. (1999). Social networks and status attainment. Annual Review of Sociology, 25, 467–487.
Lopez, N. (2003). Hopeful girls, troubled boys: Race and gender disparity in urban education. New York: Routledge.
Morgan, S. L., & Sørensen, A. B. (1999a). Parental networks, social closure, and mathematics learning: A test of Coleman’s social capital explanation of school effects. American Sociological Review, 64(5), 661–681.
Morgan, S. L., & Sørensen, A. B. (1999b). Theory, measurement, and specification issues in models of network effects on kearning: Reply to Carbonaro and to Hallinan and Kubitschek. American Sociological Review, 64(5), 694–700.
Morgan, S. L., & Todd, J. J. (2009). Intergenerational closure and academic achievement in high school: A new evaluation of Coleman’s conjecture. Sociology of Education, 82(3), 267–285.
Morrow, V. (1999). Conceptualising social capital in relation to the well-being of children and young people: A critical review. The Sociological Review, 47, 744–765.
Mueller, W., & Shavit, Y. (1998). The institutional embeddedness of the stratification process: A comparative study of qualifications and occupations in thirteen countries. In W. Mueller & Y. Shavit (Eds.), From School to work: A comparative study of educational qualifications and occupational destinations (pp. 1–45). Oxford: Clarendon Press.
New York City Department of Education. (2013). Expanded Success Initiative. New York: New York Department of Education. Retrieved from http://schools.nyc.gov/Offices/ESI/default.htm.
Noguera, P. (2008). The trouble with black boys and other reflections on race, equity, and the future of public education. San Francisco: Jossey-Bass.
Perez, P. A., & McDonough, P. M. (2008). Understanding Latina and Latino college choice: A social capital and chain migration analysis. Journal of Hispanic Higher Education, 7, 249–265.
Perna, L. W., & Titus, M. A. (2005). The relationships between parental involvement as social capital and college enrollment: An examination of racial/ethnic group differences. The Journal of Higher Education, 76(5), 485–518.
Qian, Z., & Blair, S. L. (1999). Racial/ethnic differences in educational aspirations of high school seniors. Sociological Perspectives, 42, 605–625.
Riegle-Crumb, C. (2010). More girls go to college: Exploring the social and academic factors behind the female postsecondary advantage among Hispanic and white students. Research in Higher Education, 51(6), 573–593.
Rosenbaum, J. E. (2001). Beyond college for all: Career paths for the forgotten half. New York: Russell Sage Foundation.
Royston, P., & White, I. R. (2011). Multiple imputation by chained equations (MICE): Implementation in Stata. Journal of Statistical Software, 45(4), 1–20.
Rubin, D. B. (1987a). A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest: The SIR algorithm. Journal of the America Statistical Association, 82(398), 543–546.
Rubin, D. B. (1987b). Multiple imputation for nonresponse in surveys. New York: Wiley.
Sax, L. J. (2007). College women still face many obstacles in reaching their full potential. Chronicle of Higher Education, 54(5), B46.
Schafer, J. L. (1997). Analysis of incomplete multivariate data. London: Chapman & Hall.
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177.
Shapiro, C. A., & Sax, L. J. (2011). Major selection and persistence for women in STEM. New Directions for Institutional Research, 2011(152), 5–19.
Sommers, C. H. (2000). The war against boys. The Atlantic Monthly, 285, 59–74.
Sommers, C.H. (2013, February 12). Boys at the back. New York Times, pp. SR1.
Stage, F. K., & Hossler, D. (1989). Differences in family influences on college attendance plans for male and female ninth graders. Research in Higher Education, 30(3), 301–315.
Steelman, L. C., Powell, B., Werum, R., & Carter, S. (2002). Reconsidering the effects of sibling configuration: Recent advances and challenges. Annual Review of Sociology, 28, 243–269.
Stiggins, R. J., & Conklin, N. (1992). In teachers’ hands: Investigating the practices of classroom assessment. Albany, NY: State University of New York Press.
Van Buuren, S., Boshuizen, H. C., & Knook, D. L. (1999). Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in Medicine, 18(6), 681–694.
Way, N. (2004). Intimacy, desire, and distrust in the friendships of adolescent boys. In J. Chu & N. Way (Eds.), Adolescent boys: Exploring diverse cultures of boyhood (pp. 78–104). New York: NYU Press.
Way, N. (2011). Deep secrets: Boys’ friendships and the crisis of connection. Cambridge, MA: Harvard University Press.
Wells, R. S., Seifert, T. A., Padgett, R. D., Park, S., & Umbach, P. D. (2011). Why do more women than men want to earn a four-year degree? Exploring the effects of gender, social origin, and social capital on educational expectations. Journal of Higher Education, 82(1), 1–32.
White House Task Force to Protect Students from Sexual Assault. (2014). Not alone: The first report of the White House Task Force to protect students from sexual assault. Washington, DC.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Model with set of two-way interactions of social capital with race/ethnicity | Model with set of two-way interactions of social capital with SES | |||||||
|---|---|---|---|---|---|---|---|---|
b coeff | SE | t | p | b coeff | SE | t | p | |
F2EVRATT | ||||||||
BYFEMALE | 0.295 | 0.068 | 4.314 | 0.000 | 0.281 | 0.07 | 4.019 | 0.000 |
BLACK | −0.037 | 0.994 | −0.037 | 0.971 | 0.652 | 0.105 | 6.189 | 0.000 |
ASIAN | 2.657 | 1.231 | 2.159 | 0.033 | 0.848 | 0.183 | 4.644 | 0.000 |
HISPANIC | −0.155 | 0.936 | −0.166 | 0.869 | 0.412 | 0.121 | 3.399 | 0.001 |
OTHER | −2.857 | 1.648 | −1.733 | 0.085 | −0.031 | 0.145 | −0.216 | 0.829 |
BYMOTHED | 0.06 | 0.028 | 2.131 | 0.036 | 0.057 | 0.028 | 2.030 | 0.046 |
BYFATHED | 0.043 | 0.024 | 1.829 | 0.072 | 0.046 | 0.023 | 1.962 | 0.054 |
BYSTLNG2NEW | −0.171 | 0.082 | −2.100 | 0.047 | −0.172 | 0.09 | −1.911 | 0.076 |
BYMANDF | 0.288 | 0.074 | 3.877 | 0.000 | 0.278 | 0.07 | 3.969 | 0.000 |
BYSES2 | 0.373 | 0.098 | 3.807 | 0.000 | −0.026 | 0.581 | −0.045 | 0.964 |
MIDWEST | −0.189 | 0.113 | −1.672 | 0.100 | −0.183 | 0.114 | −1.609 | 0.113 |
SOUTH | −0.471 | 0.100 | −4.716 | 0.000 | −0.462 | 0.099 | −4.654 | 0.000 |
WEST | −0.415 | 0.128 | −3.234 | 0.001 | −0.39 | 0.124 | −3.135 | 0.002 |
BYSIBHOM | −0.128 | 0.037 | −3.480 | 0.007 | −0.124 | 0.036 | −3.416 | 0.008 |
URBAN | 0.159 | 0.079 | 2.002 | 0.048 | 0.156 | 0.078 | 1.982 | 0.05 |
RURAL | −0.029 | 0.083 | −0.349 | 0.728 | −0.035 | 0.087 | −0.403 | 0.689 |
Standardized test score | 0.040 | 0.005 | 8.951 | 0.000 | 0.04 | 0.004 | 9.287 | 0.000 |
Student to parent: engages in academic discussions | 0.493 | 0.107 | 4.616 | 0.000 | 0.413 | 0.084 | 4.907 | 0.000 |
Student to parent: engages in structured activities | 0.345 | 0.109 | 3.171 | 0.005 | 0.252 | 0.100 | 2.519 | 0.030 |
Student to parent: engages in unstructured activities | −0.122 | 0.104 | −1.169 | 0.244 | 0.029 | 0.084 | 0.348 | 0.728 |
Student to parent: provides advice | 0.194 | 0.133 | 1.454 | 0.165 | 0.106 | 0.088 | 1.206 | 0.233 |
Student to parent: engages in school-related monitoring | −0.341 | 0.133 | −2.565 | 0.011 | −0.153 | 0.127 | −1.207 | 0.248 |
Parent to parent: benefits | 0.094 | 0.084 | 1.114 | 0.28 | 0.132 | 0.064 | 2.051 | 0.053 |
Parent to parent: knows student’s 1st friend’s parents | 0.155 | 0.151 | 1.024 | 0.311 | 0.019 | 0.102 | 0.185 | 0.853 |
Parent to parent: knows student’s 3rd friend’s parents | −0.031 | 0.101 | −0.308 | 0.758 | −0.051 | 0.088 | −0.583 | 0.561 |
Parent to parent: knows student’s 2nd friend’s parents | 0.178 | 0.113 | 1.58 | 0.116 | 0.144 | 0.097 | 1.474 | 0.147 |
Student to teacher: relations | −0.069 | 0.049 | −1.396 | 0.166 | −0.042 | 0.037 | −1.135 | 0.260 |
Student to teacher: ratio | 0.048 | 0.045 | 1.075 | 0.287 | 0.006 | 0.041 | 0.138 | 0.890 |
Student to student: perceived importance of friends to achieve | −0.085 | 0.120 | −0.707 | 0.484 | −0.052 | 0.086 | −0.603 | 0.548 |
Student to student: no. friends who dropped out of high school | −0.192 | 0.068 | −2.827 | 0.013 | −0.153 | 0.051 | −3.005 | 0.009 |
Student to student: no. friends who plan on 2-year college | −0.052 | 0.048 | −1.084 | 0.281 | −0.038 | 0.036 | −1.072 | 0.286 |
Student to student: no. friends who plan on 4-year college | 0.347 | 0.052 | 6.617 | 0.000 | 0.286 | 0.044 | 6.498 | 0.000 |
GPA | 0.571 | 0.031 | 18.281 | 0.000 | 0.576 | 0.03 | 19.415 | 0.000 |
Student to parent: engages in academic discussions_Black | 0.045 | 0.242 | 0.187 | 0.855 | ||||
Student to parent: engages in academic discussions_Asian | −0.344 | 0.332 | −1.036 | 0.313 | ||||
Student to parent: engages in academic discussions_Hispanic | −0.300 | 0.212 | −1.411 | 0.166 | ||||
Student to parent: engages in academic discussions_other | −0.156 | 0.322 | −0.486 | 0.631 | ||||
Student to parent: engages in structured activities_Black | −0.165 | 0.197 | −0.839 | 0.414 | ||||
Student to parent: engages in structured activities_Asian | 0.192 | 0.283 | 0.678 | 0.502 | ||||
Student to parent: engages in structured activities_Hispanic | −0.233 | 0.176 | −1.323 | 0.196 | ||||
Student to parent: engages in structured activities_other | −0.110 | 0.267 | −0.41 | 0.682 | ||||
Student to parent: engages in unstructured activities_Black | 0.209 | 0.223 | 0.934 | 0.359 | ||||
Student to parent: engages in unstructured activities_Asian | −0.207 | 0.339 | −0.611 | 0.552 | ||||
Student to parent: engages in unstructured activities_hispanic | 0.302 | 0.193 | 1.567 | 0.119 | ||||
Student to parent: engages in unstructured activities_other | 0.347 | 0.335 | 1.034 | 0.304 | ||||
Student to parent: provides advice_Black | −0.197 | 0.237 | −0.834 | 0.416 | ||||
Student to parent: provides advice_Asian | −0.448 | 0.342 | −1.309 | 0.202 | ||||
Student to parent: provides advice_Hispanic | −0.143 | 0.201 | −0.709 | 0.482 | ||||
Student to parent: provides advice_other | −0.464 | 0.345 | −1.343 | 0.18 | ||||
Student to parent: engages in school-related monitoring_Black | 0.385 | 0.291 | 1.322 | 0.206 | ||||
Student to parent: engages in school-related monitoring_Asian | 0.074 | 0.395 | 0.187 | 0.855 | ||||
Student to parent: engages in school-related monitoring_Hispanic | 0.442 | 0.211 | 2.098 | 0.037 | ||||
Student to parent: engages in school-related monitoring_other | 0.625 | 0.446 | 1.401 | 0.172 | ||||
Parent to parent: benefits_Black | −0.045 | 0.198 | −0.225 | 0.829 | ||||
Parent to parent: benefits_Asian | 0.109 | 0.258 | 0.422 | 0.677 | ||||
Parent to parent: benefits_Hispanic | 0.067 | 0.137 | 0.491 | 0.626 | ||||
Parent to parent: benefits_other | −0.013 | 0.224 | −0.058 | 0.954 | ||||
Parent to parent: knows student’s 1st friend’s parents_Black | −0.277 | 0.32 | −0.867 | 0.404 | ||||
Parent to parent: knows student’s 1st friend’s parents_Asian | 0.302 | 0.377 | 0.801 | 0.429 | ||||
Parent to parent: knows student’s 1st friend’s parents_Hispanic | 0.000 | 0.298 | 0.000 | 1.000 | ||||
Parent to parent: knows student’s 1st friend’s parents_Other | −0.263 | 0.39 | −0.674 | 0.501 | ||||
Parent to parent: knows student’s 3rd friend’s parents_Black | 0.014 | 0.218 | 0.066 | 0.947 | ||||
Parent to parent: knows student’s 3rd friend’s parent_Asian | −0.966 | 0.446 | −2.166 | 0.047 | ||||
Parent to parent: knows student’s 3rd friend’s parents_Hispanic | 0.084 | 0.225 | 0.376 | 0.711 | ||||
Parent to parent: knows student’s 3rd friend’s parents_other | −0.098 | 0.345 | −0.285 | 0.778 | ||||
Parent to parent: knows student’s 2nd friend’s parents_Black | −0.048 | 0.216 | −0.223 | 0.824 | ||||
Parent to parent: knows student’s 2nd friend’s parents_Asian | −0.133 | 0.412 | −0.323 | 0.747 | ||||
Parent to parent: knows student’s 2nd friend’s parents_Hispanic | −0.304 | 0.206 | −1.474 | 0.142 | ||||
Parent to parent: knows student’s 2nd friend’s parents_Other | −0.002 | 0.435 | −0.004 | 0.997 | ||||
Student to teacher: relations_Black | 0.130 | 0.088 | 1.473 | 0.145 | ||||
Student to teacher: relations_Asian | 0.063 | 0.148 | 0.424 | 0.672 | ||||
Student to teacher: relations_Hispanic | 0.095 | 0.088 | 1.085 | 0.28 | ||||
Student to teacher: relations_other | −0.117 | 0.153 | −0.761 | 0.448 | ||||
Student to teacher: ratio_Black | −0.055 | 0.089 | −0.626 | 0.532 | ||||
Student to teacher: ratio_Asian | 0.178 | 0.156 | 1.145 | 0.27 | ||||
Student to teacher: ratio_Hispanic | 0.037 | 0.117 | 0.316 | 0.755 | ||||
Student to teacher: ratio_other | 0.137 | 0.192 | 0.716 | 0.476 | ||||
Student to student: perceived importance of friends to achieve_Black | 0.013 | 0.192 | 0.07 | 0.944 | ||||
Student to student: perceived importance of friends to achieve_Asian | 0.026 | 0.340 | 0.078 | 0.939 | ||||
Student to student: perceived importance of friends to achieve_Hispanic | 0.006 | 0.205 | 0.027 | 0.979 | ||||
Student to student: perceived importance of friends to achieve_other | 0.455 | 0.321 | 1.418 | 0.16 | ||||
Student to student: no. friends who dropped out of high school_Black | 0.135 | 0.115 | 1.174 | 0.247 | ||||
Student to student: no. friends who dropped out of high school_Asian | −0.194 | 0.204 | −0.949 | 0.353 | ||||
student to student: no. friends who dropped out of high school_Hispanic | 0.168 | 0.093 | 1.815 | 0.074 | ||||
Student to student: no. friends who dropped out of high school_other | 0.004 | 0.175 | 0.021 | 0.983 | ||||
Student to student: no. friends who plan on 2-year college_Black | −0.027 | 0.08 | −0.337 | 0.737 | ||||
Student to student: no. friends who plan on 2-year college_Asian | 0.082 | 0.126 | 0.654 | 0.515 | ||||
Student to student: no. friends who plan on 2-year college_Hispanic | 0.027 | 0.096 | 0.284 | 0.778 | ||||
Student to student: no. friends who plan on 2-year college_other | 0.132 | 0.170 | 0.778 | 0.445 | ||||
Student to student: no. friends who plan on 4-year college_Black | −0.14 | 0.081 | −1.719 | 0.088 | ||||
Student to student: no. friends who plan on 4-year College_Asian | −0.021 | 0.147 | −0.144 | 0.886 | ||||
Student to student: no. friends who plan on 4-year college_Hispanic | −0.272 | 0.081 | −3.369 | 0.001 | ||||
Student to student: no. friends who plan on 4-year college_other | −0.014 | 0.150 | −0.095 | 0.925 | ||||
Student to parent: engages in academic discussions_ses | −0.014 | 0.109 | −0.132 | 0.895 | ||||
Student to parent: engages in structured activities_ses | −0.034 | 0.103 | −0.327 | 0.744 | ||||
Student to parent: engages in unstructured activities_ses | 0.119 | 0.123 | 0.972 | 0.334 | ||||
Student to parent: provides advice_ses | 0.063 | 0.120 | 0.526 | 0.602 | ||||
Student to parent: engages in school-related monitoring_ses | −0.089 | 0.129 | −0.694 | 0.489 | ||||
Parent to parent: benefits_ses | 0.113 | 0.096 | 1.177 | 0.256 | ||||
Parent to parent: knows student’s 1st friend’s parents_ses | −0.21 | 0.166 | −1.266 | 0.208 | ||||
Parent to parent: knows student’s 3rd friend’s parents_ses | −0.057 | 0.137 | −0.418 | 0.677 | ||||
Parent to parent: knows student’s 2nd friend’s parents_ses | 0.117 | 0.146 | 0.804 | 0.430 | ||||
Student to teacher: relations_ses | −0.065 | 0.050 | −1.293 | 0.198 | ||||
Student to teacher: ratio_ses | −0.178 | 0.052 | −3.446 | 0.001 | ||||
Student to student: perceived importance of friends to achieve_ses | 0.018 | 0.119 | 0.152 | 0.879 | ||||
Student to student: no. friends who dropped out of high school_ses | −0.073 | 0.066 | −1.11 | 0.279 | ||||
Student to student: no. friends who plan on 2-year college_ses | 0.029 | 0.059 | 0.482 | 0.633 | ||||
Student to student: no. friends who plan on 4-year college_ses | 0.074 | 0.049 | 1.506 | 0.134 | ||||
_cons | −4.468 | 0.691 | −6.469 | 0.000 | −4.949 | 0.620 | −7.981 | 0.000 |
Significance test for set of two-way interactions | F(60,248.1) = 1.14, p = 0.251 | F(15,205.4) = 1.51, p = 0.103 | ||||||
Rights and permissions
About this article
Cite this article
Klevan, S., Weinberg, S.L. & Middleton, J.A. Why the Boys are Missing: Using Social Capital to Explain Gender Differences in College Enrollment for Public High School Students. Res High Educ 57, 223–257 (2016). https://doi.org/10.1007/s11162-015-9384-9
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11162-015-9384-9