This article reports on a study of the causes and correlates of parole success and failure in Pennsylvania. Surveys, interviews, and focus groups were conducted with parole violators and parole successes. Data were collected on employment, housing, social relations, supervision, and parolees' responses to parole challenges. The primary correlates of parole failure were found to be antisocial attitudes, poor problem-solving and coping skills, and unrealistic expectations about life after release from prison. Contrary to expectations, this study found little evidence that job acquisition or housing were significant parole challenges. The greatest problem for parolees was managing themselves in a prosocial manner while facing demands from their environment.

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Background: Electronic health records (EHRs) are a rich source of health information; however social determinants of health, including incarceration, and how they impact health and health care disparities can be hard to extract. Objective: The main objective of this study was to compare sensitivity and specificity of patient self-report with various methods of identifying incarceration exposure using the EHR. Research Design: Validation study using multiple data sources and types. Subjects: Participants of the Veterans Aging Cohort Study (VACS), a national observational cohort based on data from the Veterans Health Administration (VHA) EHR that includes all human immunodeficiency virus–infected patients in care (47,805) and uninfected patients (99,060) matched on region, age, race/ethnicity, and sex. Measures and Data Sources: Self-reported incarceration history compared with: (1) linked VHA EHR data to administrative data from a state Department of Correction (DOC), (2) linked VHA EHR data to administrative data on incarceration from Centers for Medicare and Medicaid Services (CMS), (3) VHA EHR-specific identifier codes indicative of receipt of VHA incarceration reentry services, and (4) natural language processing (NLP) in unstructured text in VHA EHR. Results: Linking the EHR to DOC data: sensitivity 2.5%, specificity 100%; linking the EHR to CMS data: sensitivity 7.9%, specificity 99.3%; VHA EHR-specific identifier for receipt of reentry services: sensitivity 7.3%, specificity 98.9%; and NLP, sensitivity 63.5%, specificity 95.9%. Conclusions: NLP tools hold promise as a feasible and valid method to identify individuals with exposure to incarceration in EHR. Future work should expand this approach using a larger body of documents and refinement of the methods, which may further improve operating characteristics of this method.

As the US incarceration rate has reached an unprecedented level, so has the number of people leaving prison and returning to the community. Faced with the prison population growth together with the economic downturn and budget crises, many states are seeking ways to break the increasing cycle of recidivism. Although research on recidivism and desistance has not always learned from each other, recently, there is an increasing convergence of these two streams of research. This convergence has been stimulated by a variety of factors, but most notably, it draws from emerging research on redemption, which focuses on the inverse relationship between recidivism risk and time since previous contact with the criminal justice system. Although the concepts of recidivism, desistance, and redemption are all about continuity and change in criminal offending over time, the relationship between the three has not been examined. In this paper, we discuss the interface between recidivism and desistance research with a particular focus on redemption research; point out one emerging consensus from both recidivism and desistance research, namely, the importance of offenders' motivation and individual internal change; and discuss new ideas to effectively improve our approaches of reducing recidivism and facilitating desistance.

In the schools of crime hypothesis, social interactions between inmates are assumed to produce criminogenic rather than deterrent prison peer effects, thus implicating them in the persistence of high recidivism rates and null or criminogenic prison effects. We assess the validity of the schools of crime hypothesis by estimating prison peer effects that result from differential cellmate associations in a male, first‐time release cohort from the Pennsylvania Department of Corrections. To isolate causal prison peer effects in the presence of essential heterogeneity, we use a semiparametric local instrumental variables estimation strategy. Our results do not support the school of crime hypothesis. In our sample, prison peer effects produced in interaction with more criminally experienced cellmates are always null or deterrent rather than criminogenic. Although we do not explicitly test for the operant conditioning mechanisms theorized to underlie social influence in the context of differential association, we argue that, under the assumption that the differential association context relates positively to the direction of peer influence, our universally noncriminogenic estimates exclude direct reinforcement, vicarious reinforcement, and direct punishment as potential drivers of prison peer effects produced in interaction with more criminally experienced cellmates. Our results support the assertion that operant conditioning mechanisms connect differential association and deterrence theories.