Article-Journal

The continuing crises of the COVID-19 pandemic and issues surrounding disparate policing practices have illuminated an underlying issue facing law enforcement agencies- how to recruit, hire, and retain qualified officers.

Employment theoretically serves as a source of informal social control that can promote desistance from crime (Sampson & Laub, 1993).

In the assessment world, risk determines “who” to treat and needs determine “what” (Bonta & Andrews, 2016).

An abundance of research has established Adverse Childhood Experiences’ (ACEs’) contributions to deviant behavior.

Research indicates non-cisgender and non-heterosexual individuals experience higher rates of intimate partner violence compared to their cisgender and heterosexual counterparts.

Risk assessments have been constructed using a variety of algorithms, from bivariate associations, to regression, to advanced machine learning (ML) approaches.

In December 2018, the First Step Act of 2018 was signed into law, which required the Federal Bureau of Prisons (BOP) to begin using risk and needs assessment to assign programs and provide inmates with required treatment.

A top priority of prison authorities is maintaining a safe and orderly institutional environment. Gangs are believed to impede this objective, warranting bespoke policies and practices.

Cybercriminals operate in obscurity to avoid detection of their illegal deeds.

Since their seminal work, Andrews and Bonta outlined the Central Eight assessment domains.