To determine how effective the current system of risk-based parole is, researchers from the UC Davis Violence Prevention Research Program and the University of Missouri, Kansas City, used machine learning to analyze parole data from New York.

The machine learning algorithm found the predicted risks for those denied parole and those released are very similar. This suggests that low-risk individuals may have remained incarcerated, while high-risk individuals were released.

During the first five months of the pandemic in 2020, low-income communities of color experienced significantly greater increases in firearm violence, homicides and assaults compared to more affluent, white neighborhoods.

Previous studies showed increases in violence in U.S. cities during the pandemic but did not indicate where violence was highest or increased most within those cities.

“We found that zip codes with higher concentrations of low-income Black people and people of color experienced substantially higher rates of violence from March to July 2020 than did zip codes with higher concentrations of high-income white people,” said Julia Schleimer, the lead author of the study and a research data analyst at VPRP.