Document Type

Dissertation

Degree

Doctor of Philosophy

Major

Criminology and Criminal Justice

Date of Defense

4-26-2011

Graduate Advisor

Richard Rosenfeld, Ph.D.

Committee

Richard Rosenfeld

Beth Huebner

Andres Rengifo

Joan Petersilia

Abstract

Numerous studies have shown that several characteristics of offenders are related to their likelihood of recidivism after release from prison. Nearly all of these studies, however, have focused on offenders from just one state. Few studies have examined recidivism rates controlling for the characteristics of offenders from multiple states, and virtually none have examined recidivism rates controlling for characteristics of offenders from multiple states during different periods of time. Additionally, few studies have explored different types of recidivism across multiple jurisdictions. To address these shortcomings, this dissertation applied logistic regression models to data from the publicly available Prisoners Released in 1994 dataset to investigate the extent to which nine individual level factors explain variation in recidivism rates within three years of release from prison across 15 states. The nine factors are: 1) gender, 2) age at first arrest, 3) race, 4) age at release, 5) number of prior arrests, 6) type of current offense, 7) time served, 8) admission type and 9) release type. Eight forms of recidivism were examined: 1) rearrest for any offense, 2) rearrest for a new violent offense, 3) rearrest for a new property offense, 4) rearrest for a new drug offense, 5) rearrest for a new public order offense, 6) reconviction probability if rearrested, 7) reimprisonment probability if reconvicted, and 8) parole violations. The dissertation investigated differences in the effects of the individual level factors on each form of recidivism. To investigate the effects of criminal justice policies and practices on state differences in recidivism rates, multilevel models were estimated that include three contextual variables, in addition to the nine individual factors. The state-level contextual variables are: 1) drug arrests per 100,000 residents, 2) police officers per 1,000 residents and 3) the arrest-offense ratio. In a final analysis, regression analyses were conducted to determine the extent to which the nine individual factors explain the increase in the three-year rearrest rates among persons released from prison in 1983 and 1994. The findings reveal that differences in individual level characteristics help to explain the variation across states for some, but not all, forms of recidivism.

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