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Paternal Incarceration and Adolescent Social Network Disadvantage

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Demography

Abstract

Previous research has suggested that adolescent peers influence behavior and provide social support during a critical developmental period, but few studies have addressed the antecedents of adolescent social networks. Research on the collateral consequences of incarceration has explored the implications of parental incarceration for children’s behavioral problems, academic achievement, health, and housing stability, but not their social networks. Using network data from the National Longitudinal Study of Adolescent Health, I find that adolescents with recently incarcerated fathers are in socially marginal positions in their schools and befriend more-marginal peers than other adolescents: their friends are less advantaged, less academically successful, and more delinquent than other adolescents’ friends. Differences in network outcomes are robust to a variety of specifications and are consistent across race and gender subgroups. This study advances the social networks literature by exploring how familial characteristics can shape adolescent social networks and contributes to the collateral consequences of incarceration literature by using network analysis to consider how mass incarceration may promote intergenerational social marginalization.

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Notes

  1. Approximately one-half of respondents nominated the maximum of five male or five female friends, and 39 % nominated five of each. Therefore, friend count may be truncated for a sizable share of respondents. Because respondents were asked to nominate friends in order of closeness, however, ties who could not be nominated should constitute less-influential and important friends. Moreover, previous research has suggested close friend groups have about five or six members (Cotterell 1996; Dunphy 1963).

  2. I focus on paternal incarceration because few respondents experienced maternal incarceration prior to Wave I (N = 232), and previous research has suggested that maternal and paternal incarceration affect children differently (Lee et al. 2013; Wildeman and Turney 2014).

  3. Network location measures (nominations received, centrality, and reach in three steps) are calculated using ties only within the respondent’s school, excluding nominations sent to and received from students in the sister school (when applicable). Consequently, these measures are calculated separately at the middle and high school level for paired sister schools but jointly for combined middle and high schools. Findings are substantively consistent when combined middle and high schools are excluded from analyses.

  4. Centrality tends to be highly correlated with network size measures because centrality is partly premised on network size. Correlations between standardized Bonacich centrality and network size measures are as follows: total friends nominated (.65), nominations received (.41), and reach in three steps (.67). These moderately high correlations reflect that these measures are conceptually related but distinct (Valente et al. 2008).

  5. The Add Health restricted access network data file includes reach in three steps. Therefore, it is easily replicable and has already been used in other publications (e.g., Gallupe and Bouchard 2015; Hatzenbuehler et al. 2012; Mundt and Zakletskaia 2014). Moreover, three steps is an appealing distance because it should be large enough to extend beyond clique members to capture liaisons and adjacent cliques (Ennett and Bauman 1993) but small enough that peers at that distance could still be reasonably expected to have some influence over the respondent (Payne and Cornwell 2007).

  6. Average friend characteristics are calculated using all nominations that could be linked to friends’ in-school surveys, including friends in the sister school. Most identifiable friend nominations (98 %) are sent to students in the respondent’s own school, however.

  7. To ensure reliability, number of nominations received, Bonacich centrality, and reach in three steps are constructed for only those students in schools with response rates of 50 % or higher (121 schools) and for friendship nominations in which both the sender and the receiver are uniquely identifiable students in the same school.

  8. For friend characteristics analyses, I limit the sample to respondents who nominated at least one identifiable friend (N = 10,146) in her school or sister school so that friends’ characteristics can be measured from in-school survey responses. Approximately 11 % of nominations were to friends not in the respondent’s school pair; another 8 % were to students whose names were not on the roster (Carolina Population Center 2001). Adolescents with recently incarcerated fathers were only marginally more likely to nominate individuals not on school rosters as friends.

  9. Network data are collected again at Wave II for all respondents in 16 schools, but only nine respondents in these schools experienced paternal incarceration in the year between Waves I and II, preventing meaningful pre- and posttreatment comparison.

  10. I also used within-school nearest neighbor propensity score matching to restrict comparison to more-similar respondents, but lack of pretreatment observation of respondent characteristics and behavior pose significant challenges to credible propensity score model specification. Results are similar and available upon request.

  11. I also tried clustered standard errors and generalized estimating equation (GEE) models with exchangeable working correlation structures to account for error nonindependence within schools and found consistent results across models.

  12. Because paternal incarceration is respondent-reported, the restricted comparison group may exclude respondents who fail to report paternal incarceration at or before age 5 because they do not recall or are unaware of it. However, because respondents are presumably more likely to know about early-life paternal incarceration that was consequential for the family or long in duration, respondents inappropriately excluded from the comparison group because of incomplete information are likely less similar to the treatment group—and more similar to respondents with never-incarcerated fathers—than respondents who are aware of early-life paternal incarceration. Consequently, this potential exclusion of relevant comparison group members likely means that I underestimate differences in social network outcomes between respondents who experienced paternal incarceration shortly before Wave I and those who did not experience it after age 5.

  13. This is about twice as large as point-in-time estimates of parental incarceration in the late 1990s (Mumola 2000), which is reasonable given that I consider paternal incarceration over a three-year period.

  14. For ease of interpretation, I report linear probability model regression coefficients for isolate status. Logistic regression results are consistent.

  15. The estimated difference in number of friends nominated is likely to be biased toward 0 because of the five-person-per-gender limit on friend nominations.

  16. I tested whether the discrepancy between number of friend nominations sent and number received could be explained by depression or time spent in household and/or paid labor, in case adolescents withdraw from friendships because of increased housework or financial demands in the absence of a parent. However, adding these potential mechanisms did not change results for these or any other outcomes.

  17. In general, the magnitudes of differences in network characteristics are larger for more recent paternal incarceration and for longer duration of incarceration. The only exception is for the relationship between paternal incarceration and friends’ delinquency, which appears to be largest for respondents who experience paternal incarceration between ages 4 and 8.

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Acknowledgments

I am incredibly grateful to Bruce Western and Alexandra Killewald for their patient guidance and thoughtful feedback throughout the course of this project. I also thank Christopher Jencks, Christopher Wildeman, Dana Rotz, Steven Raphael, Becky Pettit, and participants in the Quantitative Sociology workshop, Inequality and Social Policy proseminar, and Justice and Inequality reading group at Harvard University for their helpful comments and suggestions on earlier drafts of this article. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this analysis.

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Bryan, B. Paternal Incarceration and Adolescent Social Network Disadvantage. Demography 54, 1477–1501 (2017). https://doi.org/10.1007/s13524-017-0589-8

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