Characteristics of victims of sexual abuse by gender and race in a community corrections population

The purpose of this study was to examine how victims of sexual abuse in a community corrections population differ as a result of their sex and race. Of the 19,422 participants, a total of 1,298 (6.7%) reported a history of sexual abuse and were compared with nonabused participants. The sample was analyzed by race-gender groups (White men, White women, African American men, and African American women) using univariate and logistic regression analyses, which were conducted separately for each group. White women were the most likely to report a history of sexual abuse (26.5%), followed by African American women (16.0%), White men (4.0%), and African American men (1.1%). For all groups, histories of suicidal ideation and suicide attempts were associated with a history of sexual abuse. Sexual abuse was associated with substance abuse problems for women but not the men. Cannabis dependence was associated with sexual abuse for the White women while cocaine dependence was associated with sexual abuse for the African American women. Several other variables were associated with sexual abuse for women but not men, including lower education (White women only), a history of violent offenses (White women only), and living in a shelter (African American women only). African American men tended to have higher levels of education; this was the only variable uniquely associated with either male group. Receiving psychiatric medications was associated with sexual abuse for all groups except African American men and a history of sex for drugs was associated with sexual abuse for all groups except White men. Consistent with national sample, women, particularly White women, were more likely to be victims of sexual abuse. The gender-race differences for the sociodemographic factors associated with sexual abuse, particularly the risk of substance abuse for women, suggest the need for tailored interventions for sexual abuse prevention and treatment.     

The Complexity of Hate Crime and Bias Activity: Variation across Contexts and Types of Bias

Are racially-motivated hate crimes, non-criminal bias incidents, and general forms of crime associated with the same structural factors? If so, then social disorganization, a powerful structural correlate of general crime, should predict rates of hate incidents. However, tests of social disorganization’s effects on racially-motivated hate crime yield inconsistent results. This study uses data from the Pennsylvania Human Relations Commission (PHRC) to explore such inconsistencies. Specifically, we assess the effects of social disorganization across contexts and types of bias motivation using bias incidents over 12 years. The results suggest that (a) social disorganization, particularly residential instability, is robustly correlated with rates of both hate crime and other prejudicial conduct, and that (b) the interactive effects of social disorganization help explain variations in incident rates by motivation type. Specifically, anti-black incidents are most frequent in unstable, homogeneous (i.e. white) and advantaged communities, while anti-white incidents are most frequent in unstable, disadvantaged communities.     

Campaign shocks and party support: evidence from Brazil’s 2014 presidential election

This article investigates the effect of exogenous shocks during an election cycle on electoral outcomes. Specifically, we examine the impact of the unexpected death of a prominent candidate, Eduardo Campos, in the 2014 Brazilian presidential election on support levels for the three main parties. Did the effects die out relatively quickly, providing only a temporary “bounce” or dip in support levels? Or did they alter the fundamentals of the campaign environment and produce a lasting change or “bump” in support levels that lasted until the election? Our results show that while the shock did have short-term effects on all parties’ support, it was only the party that lost its leading candidate where any longer lasting shift in support is detected; we estimate that the party received around 11 percentage points more support than they would otherwise have garnered, had Campos not died. While this was not enough to secure victory, it shows that individual candidates should be understood as a “fundamental” feature of the campaign environment, any change in which is likely to have a lasting effect on voter behavior.     

Using Private Information to Predict Homelessness Entries: Evidence and Prospects

Do people at risk of homelessness have private information—information that social service agencies cannot credibly obtain—that helps predict whether they will become homeless? This article asserts that the answer to this question is yes: homeless people and people at risk of homelessness know important things about their future. Data from Journeys Home (JH), a pathbreaking longitudinal study of people experiencing homelessness and people at risk of homelessness in Australia, are used in this article. In many cases, the private information that participants have predicts entries better than the public information that agencies can obtain. Ways in which this private information can be used to improve service delivery are suggested.     

Differential Registration Bias in Voter File Data: A Sensitivity Analysis Approach

The widespread availability of voter files has improved the study of participation in American politics, but the lack of comprehensive data on nonregistrants creates difficult inferential issues. Most notably, observational studies that examine turnout rates among registrants often implicitly condition on registration, a posttreatment variable that can induce bias if the treatment of interest also affects the likelihood of registration. We introduce a sensitivity analysis to assess the potential bias induced by this problem, which we call differential registration bias. Our approach is most helpful for studies that estimate turnout among registrants using posttreatment registration data, but it is also valuable for studies that estimate turnout among the voting‐eligible population using secondary sources. We illustrate our approach with two studies of voting eligibility effects on subsequent turnout among young voters. In both cases, eligibility appears to decrease turnout, but these effects are found to be highly sensitive to differential registration bias.     

Increasing Community College Completion Rates Among Low-Income Students: Evidence from a Randomized Controlled Trial Evaluation of a Case-Management Intervention

Community college completion rates are low, especially among low-income students. The existing policy and research attention has primarily focused on academic and financial challenges, but there is ample reason to think that non-academic obstacles might be key drivers of dropout rates for low-income students. This study focuses on the role of “life barriers” and investigates the effectiveness of intensive case-management services for low-income community college students. We evaluate the impact of the Stay the Course (STC) intensive case-management program through a multi-armed randomized controlled trial evaluation conducted between 2013 and 2016 in Fort Worth, Texas. Analysis of administrative records indicates that STC significantly increased persistence and degree completion for women; estimates for the full sample are imprecise. The statistically significant estimates for women imply that STC tripled associate's degree receipt by 31.5 percentage points. We find no difference in outcomes between students in an emergency financial assistance (EFA) only treatment arm and the control group. Given program costs of $4,343 per person, the implied cost per additional associate's degree is $27,140. This study complements existing literature on financial and informational interventions designed to increase completion rates and is most closely related to the smaller literature examining coaching and mentoring interventions.