Law Enforcement and Corrections Commons^™

Judicious Imprisonment, Gregory Jay Hall

All Faculty Scholarship

Starting August 21, 2018, Americans incarcerated across the United States have been striking back — non-violently. Inmates with jobs are protesting slave-like wages through worker strikes and sit-ins. Inmates also call for an end to racial disparities and an increase in rehabilitation programs. Even more surprisingly, many inmates have begun hunger strikes. Inmates are protesting the numerous ills of prisons: overcrowding, inadequate health care, abysmal mental health care contributing to inmate suicide, violence, disenfranchisement of inmates, and more. While recent reforms have slightly decreased mass incarceration, the current White House administration could likely reverse this trend. President Donald Trump’s and …

Mental Disorder And Criminal Justice, Stephen J. Morse

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This paper is a chapter that will appear in REFORMING CRIMINAL JUSTICE: A REPORT OF THE ACADEMY FOR JUSTICE BRIDGING THE GAP BETWEEN SCHOLARSHIP AND REFORM (Erik Luna ed., Academy for Justice 2018). The criminal law treats some people with severe mental disorders doctrinally and practically differently at virtually every stage of the criminal justice process, beginning with potential incompetence to stand trial and ending with the question of competence to be executed, and such people have special needs when they are in the system. This chapter begins by exploring the fundamental mental health information necessary to make informed judgements …

Bias In, Bias Out, Sandra G. Mayson

All Faculty Scholarship

Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic risk assessment to estimate the likelihood that a person will commit future crime. As many scholars have noted, these algorithms tend to have disparate racial impacts. In response, critics advocate three strategies of resistance: (1) the exclusion of input factors that correlate closely with race; (2) adjustments to algorithmic design to equalize predictions across racial lines; and (3) rejection of algorithmic methods altogether.

This Article’s central claim is that these strategies are at best superficial and at worst counterproductive because the source of racial inequality in risk assessment lies …