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Recidivism Forecasting Challenge


Putting the results into context

Read the paper The NIJ Recidivism Forecasting Challenge: Contextualizing the Results that contextualizes how winners’ forecasts performed in terms of accuracy and fairness, discusses the metrics used to judge entries, and provides an overview of the Challenge. 

Challenge winners were required to submit research papers that describes which variables did and did not matter to the final forecasting model, and when applicable, what type of models outperformed other models. Review the submitted papers

Read the article "Imperfect Tools: A Research Note on Developing, Applying, and Increasing Understanding of Criminal Justice Risk Assessments," published in Criminal Justice Policy Review, based on discussions during a symposium of the Challenge winners. 

The National Institute of Justice’s (NIJ) “Recidivism Forecasting Challenge” (the Challenge) aims to increase public safety and improve the fair administration of justice across the United States. In accordance with priorities set by the DOJ, NIJ supports the research, development, and evaluation of strategies to reduce violent crime, and to protect police and other public safety personnel by reducing recidivism. Results from the Challenge will provide critical information to community corrections departments that may help facilitate more successful reintegration into society for previously incarcerated persons and persons on parole.

As the research, development, and evaluation agency of the U.S. Department of Justice, NIJ invests in scientific research across diverse disciplines to serve the needs of the criminal justice community. NIJ seeks to use and distribute rigorous evidence to inform practice and policy, often relying on data analytic methods to do so. The Challenge aims to improve the ability to forecast recidivism using person- and place-based variables with the goal of improving outcomes for those serving a community supervision sentence. In addition to the Challenge data provided, NIJ encourages contestants to consider a wide range of potential supplemental data sources that are available to community corrections agencies to enhance risk determinations, including the incorporation of dynamic place-based factors, along with the common static and dynamic risk factors.

The Challenge will have three categories of contestants: students; individuals/small teams/businesses; and large businesses. NIJ will evaluate all entries on how accurately they forecast the outcome of recidivism. Recidivism is defined in this Challenge as an arrest for a new crime. To receive prize money, (114 total prizes available, up to 15 per contestant/team) winning applicants must provide a comprehensive document detailing the lessons learned about what variables did and did not matter to their final forecasting model and, when applicable, what type of models outperformed other models. Contestants are encouraged to provide additional intellectual property regarding specific techniques, weighting, or other sensitive decisions.

The Challenge uses data from the State of Georgia about persons released from prison to parole supervision for the period January 1, 2013 through December 31, 2015. Contestants will submit forecasts (percent likelihoods) of whether individuals in the dataset recidivated within one year, two years, or three years after release.

NIJ expects that new and more nuanced information will be gained from the Challenge and help address high recidivism among persons under community supervision. Findings could directly impact the types of factors considered when evaluating risk of recidivism and highlight the need to support people in specific areas related to reincarceration. Additionally, the Challenge could provide guidance on gender specific considerations and strategies to account for racial bias during risk assessment.