Neighborhood Risk Factors for Recidivism: For Whom do they Matter?

Justice‐involved people vary substantially in their risk of reoffending. To date, recidivism prediction and prevention efforts have largely focused on individual‐level factors like antisocial traits. Although a growing body of research has examined the role of residential contexts in predicting reoffending, results have been equivocal. One reason for mixed results may be that an individual’s susceptibility to contextual influence depends upon his or her accumulated risk of reoffending. Based on a sample of 2218 people on probation in San Francisco, California, this study draws on observational and secondary data to test the hypothesis that individual risk moderates the effect of neighborhood factors on recidivism. Results from survival analyses indicate that individual risk interacts with neighborhood concentrated disadvantage and disorder—and these factors increase recidivism among people relatively low in individual risk, but not those at higher risk. This is consistent with the disadvantage saturation perspective, raising the possibility that some people classified as low risk might not recidivate but for placement in disadvantaged and disorderly neighborhoods. Ultimately, residential contexts “matter” for lower risk people and may be useful to consider in efforts to prevent recidivism.     

Baby face wins? Examining election success based on candidate election bulletin via multilevel modeling

A growing body of research suggests that many voters rely on facial cues from political candidates to elect their leaders. Our study proposes that having a baby face could be an asset for a political candidate in a collectivist culture. Using election bulletin photographs from Taiwan's 2004, 2008 and 2012 legislative election, we look at the extent to which a candidate's baby face is related to election outcomes. Our multilevel modelling includes the number of candidates as Level 1 units, and the number of counties in which the candidates competed as Level 2 units. Vote share is the outcome variable. After considering the candidates' traits (perceived babyfacedness, competence, attractiveness and warmth) and background characteristics, babyfacedness was the strongest predictor of vote share. Results across three elections show consistent patterns: the more babyfaced the candidate, the greater the percentage of votes a candidate received, regardless of the candidate's gender, political affiliation or incumbency status. Babyfacedness is more influential than perceived competence, attractiveness and warmth.