Dataset

This dataset was created by UOCOEEDS

Contents

Represents return status within three years of release among incarcerated individuals released to the community during a particular calendar year. Each data record represents a release to the community as a result of completing maximum sentence, reaching conditional release date, or being approved for release by the Board of Parole. The dataset includes data about release year, county of indictment, gender, age at release, and return status.

This dataset provides information on the number of individuals released between the years of 2011-2015 and the number of individuals re-incarcerated. Below are a couple of items to note about the dataset: Recidivism is defined as a return to incarceration within three years of the formerly incarcerated individuals date of release from a state correctional institution

NIJ's Recidivism Challenge - Data Provided by Georgia Department of Community Supervision, Georgia Crime Information Center. The Challenge uses data on roughly 26,000 individuals from the State of Georgia released from Georgia prisons on discretionary parole to the custody of the Georgia Department of Community Supervision (GDCS) for the purpose of post-incarceration supervision between January 1, 2013 and December 31, 2015. This is the dataset of all individuals (training and test) with all variables released.

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.

This data collection examines the relationship between individual characteristics and recidivism for two cohorts of inmates released from North Carolina prisons in 1978 and 1980. The survey contains questions on the background of the offenders, including their involvement in drugs or alcohol, level of schooling, nature of the crime resulting in the sample conviction, number of prior incarcerations and recidivism following release from the sample incarceration. The data collection also contains information on the length of time until recidivism occurs.

Three different measures of recidivism (rearrest, reincarceration, and overall recidivism) have been used by the DOC in a recent report to further explore the effects of recidivism on the criminal justice system. The DOC defines rearrest as: “the first instance of arrest after the individual is released from the custody of the DOC.” The DOC defines reincarceration as: “the first instance of returning to the custody of the DOC after the individual is released from the DOC.” The DOC defines overall recidivism as: “the first instance of any type of rearrest or reincarceration after the individual is released from the DOC.”

• The 3-year rearrest rates have been consistently higher than the 3-year reincarceration rates.
• The overall recidivism rates have remained relatively stable.
• From 2000 to 2013, rearrest rates appear to grow consistently before trending downward in recent years (e.g. 3-year rate has been below 50.0% in 4 of the last 5 years).
• The 2013 3-year reincarceration rate was down slightly at 43.7%, still lower than all the 3-year rates prior to 2008.
• The 2013 3-year overall recidivism rate dropped to 60.9%. This was the second lowest overall recidivism rate in the past 13 years (with 2011 being lowest at 59.9%)
• The 2015 1-year rates were all up slightly.

These statistics are based on a cohort of inmates.

Port of the compas-recidivism dataset from propublica (github here). See details there and use carefully, as there are serious known social impacts and biases present in this dataset. Basic preprocessing done by the imodels team in this notebook. The target is the binary outcome is_recid.

  Sample usage

Load the data: from datasets import load_dataset

dataset = load_dataset("imodels/compas-recidivism") df = pd.DataFrame(dataset['train']) X = df.drop(columns=['is_recid']) y =… See the full description on the dataset page: https://huggingface.co/datasets/imodels/compas-recidivism.

The NLSY97 standalone data files are intended to be used by crime researchers for analyses without requiring supplementation from the main NLSY97 data set. The data contain age-based calendar year variables on arrests and incarcerations, self-reported criminal activity, substance use, demographic variables and relevant variables from other domains which are created using the NLSY97 data. The main NLSY97 data are available for public use and can be accessed online at the NLS Investigator Web site and at the NACJD Web site (as ICPSR 3959). Questionnaires, user guides and other documentation are available at the same links. The National Longitudinal Survey of Youth 1997 (NLSY97) was designed by the United States Department of Labor, comprising the National Longitudinal Survey (NLS) Series. Created to be representative of United States residents in 1997 who were born between the years of 1980 and 1984, the NLSY97 documents the transition from school to work experienced by today's youths through data collection from 1997. The majority of the oldest cohort members (age 16 as of December 31, 1996) were still in school during the first survey round and the youngest respondents (age 12) had not yet entered the labor market.

This data collection provides comprehensive criminal history data on prisoners released from custody in 1983. Precise estimates are supplied on recidivism among prisoners of all ages with all types of postrelease supervision. Data cover recidivism both within and outside the states in which the prisoners were released. Variables include sociodemographic indices, type of sentence, length of sentence, offense, court action, and date of court action.

The rate of recidivism of sentenced prisoners in Finland fluctuated over the period from 2009 to 2018. 76 percent of sentenced prisoners released in 2018 who had six or more previous prison sentences returned to prison within a five-year follow-up period. The corresponding share among prisoners with one previous sentence was 41 percent.

Decrease the percentage of offenders returning to prison within 36 months of release from 21.2% in 2013 to 20.1% by 2017.

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. This study, with assistance from the National Institute of Justice's Data Resources Program (FY2012), is a reanalysis of data from the national evaluation of the federal Serious and Violent Offender Reentry Initiative (SVORI). SVORI provided funding to 69 agencies across the United States to enhance reentry programs and coordination between corrections and community services. The national evaluation covered 16 of these sites, twelve of which provided services to the 2,054 adult ex-prisoners who are the focus of the present study. The purpose of this study is to understand whether or not offenders receive the services they say they need, and whether the degree of 'fit' between this self-reported criminogenic need and services received is related to recidivism. This study analyzes data from the SVORI multisite evaluation to assess the potential explanations for the mixed effectiveness of reentry programs. The goal is to understand whether or not service-risk/need fit is related to successful reentry outcomes, or whether the needs of returning prisoners are unrelated to their risk of recidivism regardless of how well they are addressed. For the present study researchers obtained the SVORI (ICPSR 27101) outcome evaluation datasets from the National Archive of Criminal Justice Data (NACJD). The archive holds four separate datasets from the evaluation: Adult Males Data (Part 1, N=1,697), Adult Females Data (Part 2, N=357), Juvenile Males Data (Part 3, N=337) and official recidivism and reincarceration data (Part 4, N=35,469), which can be linked on a one-to-many basis with the individual-level data in the other three datasets. To prepare the SVORI data for analysis researchers merged Datasets 1 and 2 (Adult Males and Adult Females) and created seven separate datasets containing Waves 1 through 4 survey data, National Crime Information Center (NCIC) crime data, administrative data, and sampling weights. This deposit to NACJD is intended to complement the existing SVORI dataset (ICPSR 27101). It contains an R syntax file to be used with the datasets contained in the ICPSR 27101 collection.

The primary goal of this project was to increase understanding about the mechanisms and processes of desistance from crime and drug use among current urban, largely racial minority, and increasingly women criminal offenders. This research follows former drug-involved offenders for over 20 years post-release from prison in Delaware. The project was guided by Paternoster and Bushway's identity theory of desistance (2009), which relies on the concept of identity that is theorized to provide direction for an individual's behavior. The identity theory of desistance emphasizes the individual identity as reflexive, interpretive, and as such, premised on human agency. The project featured a multi-method design and unfolded in two phases. The sample for this study originated from a previous sample used to evaluate the efficacy of therapeutic communities in reducing recidivism and relapse for drug involved offenders released from Delaware prisons in the early 1990s. In Phase I of the present study, official arrest records were obtained for the previous sample of 1,250 offenders from 1956 to 2008 from both official Delaware Statistical Analysis Center (SAC) and National Crime Information Center (NCIC) data sources. From these data, race- and gender-specific offending trajectory models were estimated. In Phase II, in-depth qualitative interviews were conducted with 304 respondents selected from within the different offending trajectory groups. The goal of the interviews was to examine the processes and mechanisms that led to persistence or desistance from crime and drugs. DS1 contains NCIC and Delaware SAC arrest records for the full sample in Phase I. DS2 contains demographic information and trajectory group assignment for the Phase II interview sample participants. Qualitative data are not available for this collection.

NIJ's Recidivism Challenge - Data Provided by Georgia Department of Community Supervision, Georgia Crime Information Center. The initial test dataset is the remaining 30% of the population used in the Challenge. This dataset does not have the dependent variable as that is what you are intended to forecast.

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 Contextual Data Files: Complete.data.file.dta: 2,757 Cases, 1,055 Variables countyemployment.dta: 10,956 Cases, 6 Variables places.dta: 5,004 Cases, 5 Variables TractDataInterpolated-long.dta: 57,036 Cases, 50 Variables TractDataInterpolated-wide.dta: 2,716 Cases, 1,009 Variables tractscales2000.dta: 2,716 Cases, 49 Variables urbanicity + density.dta: 2,716 Cases, 9 Variables Demographic variables included: gender, race, educational attainment, age, employment, and marital status.

Recidivism is the act of committing another crime or coming into conflict with the criminal justice system (CJS) again. It is an important measure of the effectiveness of CJS efforts to promote rehabilitation, reintegration, and public safety. This fact sheet is based on publicly available data from the provincial governments of Ontario and Québec, the Correctional Service of Canada (CSC), Public Safety Canada (PSC), and Statistics Canada. The data were collected from 2001 to 2016.

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.

description: This dataset reports whether an offender is re-admitted to prison or not within three years from being released from prison in Iowa. The recidivism reporting year is the fiscal year (year ending June 30) marking the end of the three year tracking period. The Department of Corrections uses recidivism as an indicator on whether strategies are reducing offenders relapse into criminal behavior. A three year time frame is used as studies have shown if an offender relapses into criminal behavior it is most likely to happen within three years of being released.; abstract: This dataset reports whether an offender is re-admitted to prison or not within three years from being released from prison in Iowa. The recidivism reporting year is the fiscal year (year ending June 30) marking the end of the three year tracking period. The Department of Corrections uses recidivism as an indicator on whether strategies are reducing offenders relapse into criminal behavior. A three year time frame is used as studies have shown if an offender relapses into criminal behavior it is most likely to happen within three years of being released.