Law.com: UC criminologist explains risk assessment tools
Risk assessment tools are used across the U.S. to assign scores to defendants or convicted offenders based on the likelihood they will recommit crimes, fail to appear at pretrial hearings or commit a crime before those hearings. But, implemented in different jurisdictions, the same risk assessment tool can yield vastly different results, reports Law.com. Helping to shed light on the seeming discrepancy is University of Cincinnati criminologist Ed Latessa, a professor of criminal justice in the College of Education, Criminal Justice, and Human Services.
One common misconception about assessment tools is that they predict an individual’s recidivism or pretrial risk, Latessa explains. In reality, “they‘re not predicting [an] individual, they’re predicting a group,” said Latessa, who helped develop the Ohio Risk Assessment System (ORAS).
He adds, “A judge thinks if you’re standing in front of them and you scored low risk, you’re not going to [recidivate]. No—that just means you’re in a group with a low percentage of failure.”
Read the full story here.
Featured image at top: Handcuffs stock image, provided by Law.com
Related Stories
Sugar overload killing hearts
November 10, 2025
Two in five people will be told they have diabetes during their lifetime. And people who have diabetes are twice as likely to develop heart disease. One of the deadliest dangers? Diabetic cardiomyopathy. But groundbreaking University of Cincinnati research hopes to stop and even reverse the damage before it’s too late.
Is going nuclear the solution to Ohio’s energy costs?
November 10, 2025
The Ohio Capital Journal recently reported that as energy prices continue to climb, economists are weighing the benefits of going nuclear to curb costs. The publication dove into a Scioto Analysis survey of 18 economists to weigh the pros and cons of nuclear energy. One economist featured was Iryna Topolyan, PhD, professor of economics at the Carl H. Lindner College of Business.
App turns smartwatch into detector of structural heart disease
November 10, 2025
An app that uses an AI model to read a single-lead ECG from a smartwatch can detect structural heart disease, researchers reported at the 2025 Scientific Sessions of the American Heart Association. Although the technology requires further validation, researchers said it could help improve the identification of patients with heart failure, valvular conditions and left ventricular hypertrophy before they become symptomatic, which could improve the prognosis for people with these conditions.