Assessing the Efficiency of Home Electronic incarceration as an Alternative to Custodial Confinement; Assessing the Impact of Educational Programs on Inmates with Life Sentences

Phillips, Laura, School of Engineering and Applied Science, University of Virginia
Davis, William, University of Virginia
Seabrook, Bryn, University of Virginia
Smith, Michael, EN-CEE, University of Virginia
White, K., University of Virginia
Alonzi, Loreto, DS-Faculty Affairs, University of Virginia

Both my capstone project, focusing on Home Electronic Incarceration, and my thesis topic, looking into educational programs within the jail setting, are centered around the theme of rehabilitation. The goals of both of these programs is to better the well-being of inmates both while in prison and as they reenter society. However, my thesis focuses on the population of inmates who are not expected to be released back into society while my capstone analysis is only looking at those inmates with low-risk crimes who are expected to serve less than 3 years of jail and includes individuals who will almost certainly return back into the community.

Capstone Overview:
Home Electronic Incarceration, HEI, is a program within the US criminal justice system that allows inmates to serve their sentence from their residence rather than in jail. In hopes of decreasing infection rates, Albemarle Charlottesville Regional Jail significantly increased their capacity for HEI during the pandemic. Prior capstone groups have performed data analysis and discovered that those offenders who served their sentence on HEI were less likely to reoffend when compared to those inmates serving traditional sentences at ACRJ. Currently there is a manual process for determining those who should be on HEI. In hopes of streamlining the process and increasing the number of individuals receiving HEI services, this year's team will investigate factors that correlate with success on HEI. The factors the team will analyze are age, sex, race, number of dependents as well as education level and employment status if possible. Differences in any of these factors within HEI recidivism will then be compared to differences found within the traditional custody pattern at ACRJ.

STS Summary:
In recent years, the United States criminal justice system has emphasized the need for jails and other correctional facilities to serve as places for rehabilitation. One popular sector of rehabilitation programs are educational programs such as GED and college credit programs. These programs have been proven to decrease recidivism rates and increase employment options for inmates once released from jail, however there is little research analyzing the impacts of educational programs on those inmates who are serving life-long sentences or at risk of the death penalty. This paper explores the possible impacts this subset of inmates may face by focusing on self-esteem, motivation and mental health and is examined using the ethical theories of deontology and consequentialism. These findings will help policy makers aid decisions around the formation of these educational programs and will help correctional facilities decide which inmates are eligible for educational programs.

Before performing data analysis that has the potential to affect the criminal justice
system, it is crucial to understand how the system works. Reading studies pertaining to the history of the criminal justice system, the policies that create the system and all the biases that are present is important to consider when drawing conclusions on data that is built off of a complex and biased system. Also, reading and watching interviews following inmates' experiences in different programs for my STS topic helps to better understand the experience the people behind the numbers in our data analysis represent. In addition, one section of the capstone is focused on how education status impacts recidivism rates for those individuals placed on HEI. Through my STS research, I am able to approach the analysis of this section better by understanding the structure and intentions of these programs to all parties involved.

BS (Bachelor of Science)

School of Engineering and Applied Science, Bachelor of Science in Systems and Information Engineering, Technical Advisor: Michael Smith, Loreto Alonzi, Preston White, STS Advisor: Bryn Seabrook, Technical Team Members: Stella Banino, George Boulos, Chris Craft, Sally Sydnor

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