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Although recent years have seen a dramatic increase in research on the relationship between space and crime, few studies have examined the impact of space on the juvenile justice outcomes of treatment non-completion and recidivism. Fewer yet have investigated how such effects might differ on those outcomes when disaggregated by the reason for non-completion and recidivism offense type. This study seeks to address those theoretical gaps by determining the effects of distance to treatment for juvenile offenders on type of treatment non-completion and recidivism. By estimating the effects of not only linear and temporal distance, but also social distance, this analysis represents a valuable inquiry into the influence of space on juvenile offenders. Data on juvenile offenders adjudicated in Philadelphia's Family Court to attend community-based treatment from 1996 through 2002 provide this study with 6,208 individual units of analysis. Data describing the neighborhoods in which the juveniles live and the programs that they attend are also included in this analysis. The use of hierarchical linear models allows for the simultaneous estimation of multiple levels of control variables when modeling the effects of distance to treatment. Separate models are constructed to estimate the direct effects of distance to treatment on treatment non-completion and then the subsequent, indirect effects of distance to treatment on juvenile recidivism. Results from two-level models that control for both neighborhood and program context indicate that distance to treatment does influence the likelihood of both treatment non-completion and recidivism. In general, distance to treatment was found to increase the likelihood of both treatment non-completion and recidivism as distance to treatment increases. Interaction effects that represent the joint effects of distance and race indicate that the impact of distance is generally greater for non-Whites, as they are more likely than Whites to fail to complete treatment as distance increases. Results from cross-classified models reveal limitations of the data related to statistical power and noise. Findings from this analysis contribute to several bodies of literature, including criminology and geography, and strongly support the consideration of distance to treatment by policymakers within the juvenile justice system. / Criminal Justice

Considering that approximately two-thirds of individuals who are released from prison are re-arrested at least once within three years following release (Langan and Levin 2002), any research that seeks to identify factors associated with successful reentry is certainly warranted. This dissertation investigates the role of family support for individuals who have been deemed serious and violent offenders and recently released from state prisons. Little research has sought to quantitatively measure the extent of the relationship between levels of family support and recidivism after controlling for other known predictors of reoffending. Prior research has largely relied on fairly small sample sizes, short follow-up periods post-release, basic bivariate analyses and inconsistent conceptualizations of family support (La Vigne, Visher and Castro 2004; Nelson, Deess and Allen 1999; Sullivan, Mino, Nelson and Pope 2002; Visher, La Vigne and Travis 2004b). As part of the evaluation of the Serious and Violent Offender Reentry Initiative (SVORI), 1,697 adult males and 357 adult females were interviewed 30 days prior to their release and then three, nine and 15 months following release. Using the data collected from these interviews, this dissertation explores the relationship between emotional family support and instrumental family support and four measures of reoffending: any self-reported criminal offending, any self-reported violent offending, any self-reported drug offending and whether any arrest occurred (using official records from the National Crime Information Center) during each of the post-release follow-up periods. Controlling for other known predictors of reoffending, logistic regression models are used to predict the likelihood of reoffending. Considering respondent attrition over successive interview waves, all analyses are conducted using listwise deletion as well as multiple imputation to handle missing data. Results generally reveal that emotional support is associated with a significant decrease in reoffending, while instrumental support is not significantly associated with reoffending. These findings have implications for correctional policies and programming, sentencing policies, post-release supervision policies and programming, criminological theory and future research. / Criminal Justice