This survey assesses the impact of a determinant sentencing law, the Fair Sentencing Act, which became effective July 1, 1981, in North Carolina. Specific variables include information from official court records on witness testimony and quality of evidence, information from prison staff and probation/parole officers, and social, demographic, and criminal history for defendants. In this dataset it is also possible to trace defendants through the criminal justice system from arrest to disposition.

The purpose of this data collection was to measure the validity or accuracy of four recidivism prediction instruments: the INSLAW, RAND, SFS81, and CGR scales. These scales estimate the probability that criminals will commit subsequent crimes quickly, that individuals will commit crime frequently, that inmates who are eligible for release on parole will commit subsequent crimes, and that defendants awaiting trial will commit crimes while on pretrial arrest or detention. The investigators used longitudinal data from five existing independent studies to assess the validity of the four predictive measures in question. The first data file was originally collected by the Vera Institute of Justice in New York City and was derived from an experimental evaluation of a jobs training program called the Alternative Youth Employment Strategies Project implemented in Albuquerque, New Mexico, Miami, Florida, and New York City, New York. The second file contains data from a RAND Corporation study, EFFECTS OF PRISON VERSUS PROBATION IN CALIFORNIA, 1980-1982 (ICPSR 8700), from offenders in Alameda and Los Angeles counties, California. Parts 3 through 5 pertain to serious juvenile offenders who were incarcerated during the 1960s and 1970s in three institutions of the California Youth Authority. A portion of the original data for these parts was taken from EARLY IDENTIFICATION OF THE CHRONIC OFFENDER, [1978-1980: CALIFORNIA] (ICPSR 8226). All files present demographic and socioeconomic variables such as birth information, race and ethnicity, education background, work and military experience, and criminal history, including involvement in criminal activities, drug addiction, and incarceration episodes. From the variables in each data file, standard variables across all data files were constructed. Constructed variables included those on background (such as drug use, arrest, conviction, employment, and education history), which were used to construct the four predictive scales, and follow-up variables concerning arrest and incarceration history. Scores on the four predictive scales were estimated.

These data were gathered to investigate the usefulness of statistical methods, particularly multiple-regression analysis, in predicting repeat criminal activity subsequent to an individual's release from prison. The data collection consists of follow-up information, collected in 1988, on a sample of males released from California prisons. The follow-up study identified criminal activity subsequent to individuals' release from prison through 1988. Predictor variables include age, prior periods of arrest, history of drug use, seriousness of original offense, and number of arrests for nuisance, person, property, and fraud offenses.

This study examines the criminal activities of a group of young offenders after their release from prison to parole supervision. Previous studies have examined recidivism using arrests as the principal measure, whereas this study examines a variety of factors, including length of incarceration, age, sex, race, prior arrest record, prosecutions, length of time between parole and rearrest, parolees not prosecuted for new offenses but having their parole revoked, rearrests in states other than the paroling states, and the nature and location of rearrest charges. Parolees in the 22 states covered in this study account for 50 percent of all state prisoners paroled in the United States in 1978.

The purpose of the study was to quantify the effect of the embrace of DNA technology on offender behavior. In particular, researchers examined whether an offender's knowledge that their DNA profile was entered into a database deterred them from offending in the future and if probative effects resulted from DNA sampling. The researchers coded information using criminal history records and data from Florida's DNA database, both of which are maintained by the Florida Department of Law Enforcement (FDLE), and also utilized court docket information acquired through the Florida Department of Corrections (FDOC) to create a dataset of 156,702 cases involving offenders released from the FDOC in the state of Florida between January 1996 and December 2004. The data contain a total of 50 variables. Major categories of variables include demographic variables regarding the offender, descriptive variables relating to the initial crime committed by the offender, and time-specific variables regarding cases of recidivism.

Using data from RECIDIVISM OF PRISONERS RELEASED IN 1994: [UNITED STATES] (ICPSR 3355), this study developed an analytical approach to utilize detailed dated criminal arrest history information in order to investigate whether, and to what extent, incarceration is able to deter offenders from future offending. This data collection consists of the syntax for a SAS macro used to estimate individual specific offending micro-trajectories, project counterfactual trajectories, and to assess the actual post-release offending patterns against the backdrop of these counterfactuals. The arrest records of individuals were clustered in chronological order and were truncated after the first post-release re-arrest event. The key independent variables used in estimating the pre-release criminal history accumulation process included the arrest number, the age at first arrest, whether or not the individual was confined as a result of the previous arrest event, and a measure of the number of years taken to reach each arrest event cumulated through the last arrest event. The same set of basic variables were used to model first re-arrest after release (recidivism).

The current study focused on 479 men and women from South Carolina who were enrolled as participants in the Serious and Violent Offender Reentry Initiative (SVORI) multi-site program evaluation shortly before prison release in 2004 or 2005. The original SVORI data suggested that the South Carolina respondents were similar to the multi-site sample with "committed to not going back to prison" as the most common reason for desisting and using drugs or alcohol as the most common reason for persisting. The goals of the current study were to (1) update information on the current status of these individuals across multiple domains (e.g., housing, employment, substance use); (2) gather additional administrative recidivism data to examine long-term offending; and (3) acquire information about the factors individuals associated with their decisions to desist from criminal activity, as well as circumstances associated with renewed criminal activity or desistence. Interviews were conducted with those that the study team were able to locate and additional administrative arrest and incarceration data were acquired for the full sample, providing recidivism follow-up over at least a 10-year period. Official administrative data were obtained from the South Carolina Law Enforcement Division (rearrests) and South Carolina Department of Corrections (reincarcerations). Arrest data span the entire arrest history (from first arrest through December 2015); reincarceration data span the period between the SVORI study prison release in 2005 and 2006 through June 2014. These data were obtained for the full sample of 479 South Carolina SVORI participants. Three components of interview data were collected. Desistance study interview data: 1 wave of in-person interviews was conducted with 208 study subjects who consented to participate in an interview. The research team used computer-assisted personal interviewing (CAPI) to administer the survey, and interviews were conducted from September 2016 through March 2017. Life event data: The Life Events Calendar (LEC) is a tool used in qualitative and quantitative research to gather retrospective information about a person's life, experiences, and history. The approach is based on autobiographical memory and how entering events on a calendar or page help facilitate memory recall. LECs typically encompass periods of 5 years or less; this study's LEC covered a 10- to 12-year span to allow analysis since last contact with the study cohort. Data were collected from the 208 subjects who consented to be interviewed. SVORI interview data: This inventory includes files with select baseline and outcome data (e.g., self-reported employment, drug use, criminal behavior) for desistance study subjects who responded to follow-up interviews at Wave 2 (3-month), Wave 3 (9-month), and Wave 4 (15-month). This collection of administrative and interview data is organized into 14 data parts. Demographic data includes information on age, gender, race, and education.

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 the files available with this collection and consult the investigator(s) if further information is needed. Researchers compiled datasets on prison admissions and releases that would be comparable across places and geocoded and mapped those data onto crime rates across those same places. The data used were panel data. The data were quarterly or annual data, depending on the location, from a mix of urban (Boston, Newark and Trenton) and rural communities in New Jersey covering various years between 2000 and 2010. The crime, release, and admission data were individual level data that were then aggregated from the individual incident level to the census tract level by quarter (in Boston and Newark) or year (in Trenton). The analyses centered on the effects of rates of prison removals and returns on rates of crime in communities (defined as census tracts) in the cities of Boston, Massachusetts, Newark, New Jersey, and Trenton, New Jersey, and across rural municipalities in New Jersey. There are 4 Stata data files. The Boston data file has 6,862 cases, and 44 variables. The Newark data file has 1,440 cases, and 45 variables. The Trenton data file has 66 cases, and 32 variables. The New Jersey Rural data file has 1,170 cases, and 32 variables.

The purpose of this study was to provide a comprehensive assessment of the usefulness and effectiveness of prediction and classification of offenders under community supervision. A felony cohort data collection instrument was developed to test the validity of the Wisconsin Risk and Need Instrument in use in Texas, as well as to develop "better" predictor variables for a variety of dependent variables. Using the felony cohort data instrument, the Texas Department of Criminal Justice Community Justice Assistance Division (TDCJ-CJAD) collected detailed statewide information on 3,405 felony offenders placed on probation in Texas during October 1993. Specifically, the form was completed by a probation officer on all felony probation intakes at the time the initial case classification risk/needs assessment was conducted. Additionally, follow-up forms were developed and administered to track the offenders' progress at one year, two years, and three years. Variables include probationer information, current offense, criminal history, social history, substance abuse, probation sanctions, case classification risk items, and case classification need items. Additional variables include felony cohort one-year follow-up data form questions, felony cohort second-year follow-up data form questions, and felony cohort third-year follow-up data form questions.

recidivism rates for persons released from state prisons with specific demographic, criminal history, and sentence attributes.