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California's 2011 Public Safety Realignment created an unprecedented policy experiment by transferring the authority over lower-level felony offenders from the state correctional system to fifty-eight county jail and probation systems. While centered in California, these changes are reflective of an ongoing national conversation about the appropriate level of government at which to focus crime control efforts. In this article, we first situate Realignment in criminological and sociolegal literatures, showing how the reform offers opportunities to further inquiry as to the effectiveness of a wide variety of correctional strategies, implementation, and local variation in correctional law and policy. We then review early research focused on the statewide effect of Realignment on recidivism, which has produced mixed findings depending on the measure of recidivism applied. We then examine variation in recidivism outcomes across county sites and present findings that indicate there is an important relationship between local Realignment implementation strategies and recidivism outcomes. Throughout, we focus on two overarching themes. The first is the challenge of disentangling the roles of offender behavior from justice system response in meaningfully interpreting changes in recidivism outcomes. The second is the challenge of evaluating the effects of policy or practice changes under limited data. Although the need for better and more expansive data is a common theme, we highlight it here in the context of a larger data collection that we have under way.

This article reports rates of recidivism among initially substantiated and initially unsubstantiated child maltreatment events to determine if substantiation status is associated with higher risk of recidivism. This is an important question given recent concerns that unsubstantiated cases may have as high or almost as high a risk of recidivism as do substantiated cases. The data are analyzed at both the victim level and the case level, divided by type of maltreatment, and followed for 4.5 years. The data used are administrative and combine a series of state databases with census data. Analyses are performed at the bivariate and multivariate (Cox proportional hazards model) levels. The main finding is that unsubstantiated cases are at high risk for recidivism, in many cases as high a risk as substantiated cases. Implications for practice, policy, and research are presented with a focus on the importance of providing preventative services to unsubstantiated cases.

The current study focuses on adolescents with sex offense histories and examines sexual reoffending patterns within 2 years of a prior sex offense. We employed inductive statistical models using archival official records maintained by the Florida Department of Juvenile Justice (FDJJ), which provides social, offense, placement, and risk assessment history data for all youth referred for delinquent behavior. The predictive accuracy of the random forest models is tested using receiver operator characteristic (ROC) curves, the area under the curve (AUC), and precision/recall plots. The strongest predictor of sexual recidivism was the number of prior felony and misdemeanor sex offenses. The AUC values range between 0.71 and 0.65, suggesting modest predictive accuracy of the models presented. These results parallel the existing literature on sexual recidivism and highlight the challenges associated with predicting sex offense recidivism. Furthermore, results inform risk assessment literature by testing various factors recorded by an official institution.

State Succession — Judgments of Courts — Incorporation of Austria into German Reich — Conviction of Criminal by Court in Austria — Whether such Conviction Equivalent to Conviction Obtained in Germany — Liability to Punishment as Recidivist according to German Law.

"The campaign to tighten rent controls in California, as in every other jurisdiction where the issue is in play, relies on voters' ongoing ignorance and misunderstanding of the realities of the rental housing market." ~ Gary Galles

This article describes a generalization to a model of recidivism proposed earlier by Maltz and McCleary (1977). This modification allows the model to better fit data on recidivism that the earlier authors presented. The mathematical and logical derivation of the new model are presented as are two methods of parameter estimation. The efficacy of the model is demonstrated on Taylor's (1971) data set and is compared with earlier efforts. It is found that the old model's fit is more than 16 times worse than that ofthe new model.

Recent research on recidivism emphasizes the importance of neighborhoods to successful prisoner reentry. This research analyzes two ways in which institutions of neighborhood governance affect reentry. First, offenders in neighborhoods with institutions supporting social control may have more success in reintegrating into the community. Second, neighborhood institutions may create barriers to entry for ex-offenders more likely to reoffend. To test this, we combine Arkansas Department of Corrections data on offenders returning to Little Rock between 2004 and 2014 with geocoded data on neighborhood and homeowner associations. We analyze this data using Cox proportional hazards and two-stage residual inclusion models of recidivism hazard. We find that a significant relationship exists between recidivism hazard and neighborhood governance, but that this is attributable to nonrandom assignment of ex-offenders to neighborhoods rather than the role neighborhood organizations play in facilitating reentry.

We use a unique data set on post-release behavior of former Italian inmates to estimate the effect of prison conditions on recidivism. By combining different sources of data we exploit variation in prison conditions measured by: 1) the extent of overcrowding at the prison level, 2) the number of deaths in the facility of detention during an inmate's stay and 3) the distance of the prison from the chief town of the province where the prison is located. By considering inmates who served their sentence in a jurisdiction different from the hometown in which they live after release, we can include province of residence fixed effects and account for the main source of unobserved heterogeneity correlated to prison conditions. We find that a harsher prison treatment does not reduce former inmates' criminal activity. The extent of overcrowding and the number of deaths do not decrease the probability to be re-arrested. Instead, we find evidence that the degree of isolation measured by distance from the prison of detention to the chief town of the province where the prison is located increases recidivism. -- Crime ; prison ; deterrence