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The Real-Time Crime Forecasting Challenge sought to harness the advances in data science to address the challenges of crime and justice. It encouraged data scientists across all scientific disciplines to foster innovation in forecasting methods. The goal was to develop algorithms that advance place-based crime forecasting through the use of data from one police jurisdiction.
A 2014 LEADS scholar explains how his agency uses evidence-based research to reduce crime and better help the public
Three NIJ-funded studies can help community stakeholders better understand the complex relationship between foreclosures and crime levels in neighborhoods.
