We advance current knowledge of school punishment by examining (1) the prevalence of exclusionary discipline in elementary school, (2) racial disparities in exclusionary discipline in elementary school, and (3) the association between exclusionary discipline and aggressive behavior in elementary school. Using child and parent reports from the Fragile Families Study, we estimate that more than 1 in 10 children born 1998-2000 in large US cities were suspended or expelled by age nine, when most were in third grade. We also find extreme racial disparity; about 40% of non-Hispanic black boys were suspended or expelled, compared to 8% of non-Hispanic white or other-race boys. Disparities are largely due to differences in children's school and home environments rather than to behavior problems. Next, consistent with social stress and strain theories, we find suspension or expulsion associated with increased aggressive behavior in elementary school. This association does not vary by race but is robust to a rich set of covariates, individual fixed-effects, and matching methods. In conjunction with what we find for racial disparities, our results imply that school discipline policies relying heavily on exclusionary punishment may be fostering childhood inequality. The "culture of control" (Garland 2001) that led to unprecedented levels of incarceration in the United States has also contributed to high rates of exclusionary school discipline. More

Past cohorts of teenagers who spent long hours in jobs were more likely to drop out of high school than those who worked moderate hours or did not work at all. This article examines the association between employment intensity and dropout among adolescents in the High School Longitudinal Study of 2009 who traversed high school during a time of decreased prevalence of both employment and dropout relative to earlier cohorts. Analyses reveal that a relatively small percentage of teenagers nowadays are characterized as either intensive workers or dropouts (around 11% each). Yet, despite declines in intensive employment and dropout, disadvantaged youth remain overrepresented in both groups, and intensive work is still a risk factor for poor grades and dropout.

The current study compares estimates of peer influence from an analytic approach that explicitly address network processes with those from traditional approaches that do not. Using longitudinal network data from the PROmoting School–community–university Partnerships to Enhance Resilience peers project, we obtain estimates of social influence on multiple outcomes from both conventional linear modeling approaches and the stochastic actor–based modeling approach of the simulation investigation for empirical network analysis (SIENA) software. Our findings indicate that peer influence estimates from SIENA are not more conservative relative to other methods, that each method is subject to omitted variable bias from stable individual differences, and that imprecision among each method could lead to erroneous conclusions in samples that lack sufficient power. Together, these results underscore the difficulty in obtaining estimates of peer influence from observational data, and they give no indication that results from conventional methods tend to be biased toward overestimating peer influence, relative to SIENA.

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