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These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.

The purpose of the study was to:

• Describe the prosecution and sentencing histories for domestic violence and other offenses;
• Determine the severity gap in prosecution and sentencing between these domestic violence and non-domestic violence over a six year period; and
• To answer whether the variation in prosecution and sentencing severity predicts being subsequently charged for domestic violence in the future.

Rhode Island was selected as the study site because it has a high domestic violence arrest rate and specifically distinguishes domestic violence from non-domestic violence offenses based on the relationships of the parties, not by specific type of crime. Further, Rhode Island's judiciary maintains a public web-based database, called CourtConnect, that includes an index of defendants by name and date of birth and lists all arrests followed by prosecution and court actions through final sentence. The criminal history information includes all charges filed in any Rhode Island court for the last 25 years.

Two researchers independently coded offender data (Differential Sentencing Data - Persons, n=982) available on CourtConnect. Coders then determined whether the defendants were prosecuted for the charges brought against them (Differential Sentencing Data - Offenses, n=6,649). Offenses that were not prosecuted were differentiated from offenses that were prosecuted. Each charge was classified as domestic violence or non-domestic violence as defined by state statute.

These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.

The California correctional system underwent a dramatic transformation under California's Public Safety Realignment Act (AB 109) in 2011, a law that shifted from the state to the counties the responsibility for monitoring, tracking, and incarcerating lower level offenders previously bound for state prison. Realignment, therefore, presents the opportunity to witness 58 natural experiments in the downsizing of prisons. Counties faced different types of offenders, implemented different programs in different community and jail environments, and adopted differing sanctioning policies. This study examines the California's Public Safety Realignment Act's effect on counties' criminal justice institutions, including the disparities that result in charging, sentencing, and resource decisions.

In order to investigate whether reductions to sentence length reduce recidivism and its related costs, the research team conducted two studies under the same NIJ grant.

In Study 1, the research team used a quasi-experimental approach to examine how sentence length influenced time to rearrest. Specifically, the team estimated an instrumental variable hazard model using variation stemming from the implementation of South Dakota's Public Safety Improvement Act of 2013 (SB70). SB70 was a major sentencing reform that reduced the likelihood of incarceration and the length of sentence for certain non-violent offenses. The legislation was a response to high rates of incarceration and rising criminal justice costs with a particular focus on addressing individuals convicted of non-violent offenses. The goal was to improve public safety while reducing corrections spending. For grand theft below $5,000 and third-degree burglary, the reform reduced the severity of the felony class and the maximum allowed sentence length by 50% to 80%. Only certain offenses were subject to sentencing reductions such that unaffected offense types were included in the analysis as a comparison group.

In Study 2, the research team applied the logic of recurring event hazard models that predicted the probability of events over time with two distinct objectives: to identify desisters and to estimate the impact of life events on the longitudinal pattern of offending. Administrative data from the North Carolina Department of Public Safety (NCDPS) Division of Adult Correction were obtained to answer this research question. The team connected commonly used trajectory models to recurrent event survival models.

This collection contains only syntax files and documentation that were created for Study 1 (South Dakota). The P.I. codebook reflects the dataset that was created for analysis, though the data are not available. Please refer to the User Guide for more information. While Study 2's (North Carolina) methodology is described, please note that, excluding the NIJ Final Report, no Study 2 materials are available through ICPSR.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of files available with this collection and consult the investigator(s) if further information is needed.

The Michigan Study of Life After Prison examined the association between neighborhood context and outcomes related to employment and recidivism among the cohort of former prisoners released on parole from Michigan state prisons in one calendar year (2003), controlling for pre-incarceration neighborhood context, local labor market conditions, and a large set of individual characteristics. The primary goals of this study were to answer two questions: (1) "Are ex-offenders who are released to more disadvantaged neighborhoods (those with greater poverty, unemployment, residential turnover, etc.) more likely to recidivate?" (2) "Are ex-offenders who are released to more disadvantaged neighborhoods less likely to gain stable employment?" This research sought to supplement available literature on prisoner reentry and criminal desistance, which the researchers posit existing literature has largely ignored the role that neighborhoods play in shaping the recidivism and employment of returning prisoners.

The 31 data files included as part of this collection are as follows:

Cleaned Data Files:

• casenotearrestsreps1-4_ICPSR-EDITED.dta: 4,932 Cases, 12 Variables
• casenotearrestsreps5-8_ICPSR-EDITED.dta: 5,302 Cases, 13 Variables
• casenotearrestsrep9_ICPSR-EDITED.dta: 2,321 Cases, 13 Variables
• casenoteemploymentreps1-4_ICPSR-EDITED.dta: 4,871 Cases, 28 Variables
• casenoteemploymentreps5-8_ICPSR-EDITED.dta: 4,754 Cases, 23 Variables
• casenoteemploymentrep9_ICPSR-EDITED.dta: 2,610 Cases, 23 Variables
• cleanedcasenoteaddressesreps1-8_ICPSR-EDITED.dta: 50,207 Cases, 72 Variables
• cleanedcasenoteaddressesrep9_ICPSR-EDITED.dta: 10,309 Cases, 69 Variables
• preprisonaddress_all_ICPSR-EDITED.dta: 5,183 Cases, 30 Variables
• preprisonaddress_all_rep9_ICPSR-EDITED.dta: 1,017 Cases, 63 Variables
• postprisads_ICPSR-EDITED.dta: 11,064 Cases, 41 Variables
• cleaned-demographics-population_ICPSR-EDITED.dta: 11,064 Cases, 57 Variables
• simplecrimhistory.dta: 11,064 Cases, 4 Variables
• popSAhistory.dta: 11,064 Cases, 8 Variables
• deathdates_ICPSR-EDITED.dta: 308 Cases, 3 Variables
• popprisonenterdates.dta: 11,064 Cases, 7 Variables
• discharge dates.dta: 7,369 Cases, 5 Variables
• parole and release dates for pop.dta: 11,064 cases, 3 Variables
• mdoc_recidivism_measures.dta: 11,064 Cases, 6 Variables
• recidivism dates from transits.dta: 11,064 Cases, 8 Variables
• recidivism from bir.dta: 11,064 Cases, 3 Variables
• sample marker.dta: 3,689 Cases, 2 Variables
• samplereps.dta: 3,689 Cases, 2 Variables
• tta_rsid_rep.dta: 1,363 Cases, 2 Variables