Research and development
Accounting for Racial Bias in Recidivism Forecasting, Year 3 Male Parolees Report, SAS Institute Inc. Team
Report on NIJ Recidivism Forecasting Challenge
Forecasting Recidivism: Mission Impossible
National Institute of Justice Recidivism Challenge Report: Team Aurors
Skynet is Alive and Well: Leveraging a Neural Net to Predict Felon Recidivism
NIJ Recidivism Challenge Report: Team Smith
National Institute of Justice Recidivism Forecasting Challenge: Team “MCHawks” Performance Analysis
Predicting Recidivism in Georgia Using Lasso Regression Models with Several New Constructs
Recidivism Forecasting with Multi-Target Ensembles: Years One, Two and Three
NIJ Report, Team VT-ISE
National Institute of Justice's Recidivism Forecasting Challenge: Research Paper, Group MNLB
Team MattMarifelSora: NIJ Recidivism Forecasting Challenge Report
Recidivism Forecasting Challenge
National Institute of Justice's Recidivism Forecasting Challenge, SRLLC
NIJ Recidivism Challenge Report, Team Klus
Predicting Criminal Recidivism Using Specialized Feature Engineering and XGBoost
National Institute of Justice’s Forecasting Recidivism Challenge: Team “DEAP” (Final Report)
Predicting Recidivism Fairly: A Machine Learning Application Using Contextual and Individual Data
Recidivism Forecasting Challenge: Team IdleSpeculation Report
Recidivism Forecasting Using XGBoost
Recidivism Forecasting with Multi-Target Ensembles: Winning Solution for Male, Female, and Overall Categories in Year One, Team CrimeFree
Tribal Crime, Justice, and Safety, Part 2
Stacy Lee Reynolds and Christine (Tina) Crossland continue their discussion of tribal crime, justice, and safety, including how Native American persons experience crime victimization at higher rates than non-Native people and the jurisdictional complexities in responding to tribal crime, justice, and safety. Read the transcript.
Listen to the first half of Stacy and Tina’s discussion.
Reading and Resources from NIJ
Tribal-Researcher Capacity Building Grants