Recidivism

At the National Institute of Justice’s (NIJ) 2023 National Research Conference, Sanchez led a discussion on corrections research that looked beyond preventing recidivism to explore evidence-based ways of improving individual experiences and institutional culture within prisons and jails.

(Published September 30, 2021)  This report is the first in a series continuing the Commission’s research of the recidivism of federal offenders. It provides an overview of the recidivism of federal offenders released from incarceration or sentenced to a term of probation in 2010, combining data regularly collected by the Commission with data compiled from criminal history records from the Federal Bureau of Investigation (FBI).

Length of Incarceration and Recidivism

California has undertaken numerous corrections reforms in the past decade— including public safety realignment in 2011 and Proposition 47 in 2014—in hopes of reducing the prison population, maintaining public safety, and improving persistently high recidivism rates. These reforms lowered incarceration levels, and in their aftermath, crime rates have fluctuated. Recidivism rates provide another important window into public safety and the effectiveness of correctional interventions under these policy changes.

In 2019, the CSG Justice Center engaged corrections and community supervisi

In the following discussion, we describe the logical and practical problems that arise when recidivism is used as the principal outcome measure for community corrections agencies. We recognize that recidivism will always be a feature of justice policy and practice. Recidivism offers a simple and familiar outcome measure for judging the effectiveness of justice interventions. Pointing out the logical f laws of recidivism will not diminish its salience for audiences disinclined to question its utility.

Algorithms for predicting recidivism are commonly used to assess a criminal defendant’s likelihood of committing a
crime. These predictions are used in pretrial, parole, and sentencing decisions. Proponents of these systems argue that
big data and advanced machine learningmake these analysesmore accurate and less biased than humans. We show,
however, that the widely used commercial risk assessment software COMPAS is nomore accurate or fair than predictions
made by people with little or no criminal justice expertise. In addition, despite COMPAS’s collection of 137

Recent recidivism studies by the AOUSC, USSC, and BJS have brought attention to the importance of understanding the scope of reoffending in the federal probation and pre -trial services system. These studies have also brought to light how difficult it is to compare recidivism rates across agencies. Even when using similar data, discrepancies can exist based on definitional and methodological differences.

This report presents findings from a project in which researchers examined six mentoring programs in Ohio to better understand their impact on recidivism. Youth on parole and probation who received mentoring services were matched with similar youth who did not receive mentoring services. While some reductions in recidivism were found, the differences were not statistically significant. The study looked at six Ohio mentoring programs and their impact on youth recidivism.

This brief presents five key practices for successful implementation of specialized caseloads for people with co-occurring disorders. It relies on a coordinated and collaborative approach8 and reinforces the need for probation officers to have the appropriate resources to connect people to individualized treatments and supports.

GAO selected six states that varied in their adult incarceration rates and provided geographic diversity. At BOP and the six states’ departments of corrections, GAO analyzed criminal offense and incarceration and mental health care cost data and interviewed officials about strategies for reducing recidivism for inmates with serious mental illness. The results from these six states are not generalizable, but provide insights. GAO also reviewed studies that analyzed the relationship between various programs and recidivism among offenders with mental illness.

For the past 15 years, federal, state, local, and Tribal governments, as well as community-based organizations across the country, have been focused on reducing recidivism like never before. This report answers three critical questions.

This brief from the National Reentry Resource Center provides guidance for

The share of people who return to state prison three ye

In 2014, Abt Associates began work on a grant from the National Institute of Justice to evaluate the effectiveness of home and field contacts in community supervision. The study was designed to describe the varying practices of home and other field contacts in community supervision, to document their use nationwide, and to evaluate their effectiveness in maintaining public safety and promoting compliance with supervision requirements. Abt’s research is designed to address the gap in our understanding of home and field contacts as part of community supervision.

The goal of the present study was to examine the effect of two cognitive behavioral therapy programs on recidivism in a sample of chronic youthful offenders (N = 156) and to evaluate the relationship between commonly identified recidivism risk factors (i.e., prior criminal charges, parental history of criminal behavior, gang involvement, mental health diagnoses, and number of probation violations) and re-offending.

The evidence is clear that prisoners tend to be undereducated and underemployed. What if US prison systems placed a greater emphasis on improving educational and employment outcomes for prisoners? Would it improve other outcomes such as recidivism or prison misconduct? If so, to what extent? And, if US prison systems invested in more education and employment programming, would the benefits outweigh the costs?
This report addresses these questions by providing an overview of the available evidence on the effectiveness of education and employment programming.