Analyzing Efficacy of Home Electronic Incarceration on Return-to-Custody Rates for Inmates During the COVID-19 Pandemic; The Importance of Eliminating the Dual Self-Stigma of Having a Criminal Record and Mental Illness

Author:
Hankinson, Imani, School of Engineering and Applied Science, University of Virginia
Advisors:
Francisco, Pedro Augusto, EN-Engineering and Society, University of Virginia
Alonzi, Loreto, DS-Faculty Affairs, University of Virginia
Smith, Michael, EN-CEE, University of Virginia
White, K., University of Virginia
Abstract:

Home Electronic Incarceration (HEI) is a tech-enabled alternative to custodial incarceration which allows the Albemarle-Charlottesville Regional Jail (ACRJ) to monitor individuals outside of its correctional facility. In an effort to minimize the inmate population and slow the spread of COVID-19, ACRJ and the local judicial system adjusted sentencing and incarceration protocols by increasing the use of HEI (N. Goodloe, personal communication, September 12, 2022). Although ACRJ continued this trend post-pandemic, it was unknown whether the increased use of HEI had any effect on local return to custody (RTC) rates. In response to these unknowns, our capstone team completed a quantitative analysis to better understand the demographics of HEI-use by race, gender, and severity of charge. We also sorted intake histories of inmates on HEI, calculated the average length of stay by charge type, and compared post-release outcomes for HEI and non-HEI participants.

The American criminal justice system is made up of a dense network of organizations which each have different goals, values, and stakeholders. It is these organizations, and the dynamics between them, that are responsible for making decisions that affect thousands of lives on a yearly basis. Our capstone team considered a relational view of the data when forming recommendations on how to best move forward with ACRJ’s use of HEI. A relational view of the data acknowledges the limitations of our analysis due to contextual constraints (Leonelli, 2019). Our findings provided the preliminary framework needed to better understand ACRJ’s HEI-use; however, standardization of the institution’s data handling and collection process is necessary to gain a better understanding of the system, its actors, and problem frame.

In addition to understanding HEI-use within ACRJ’s jurisdictions, my STS research seeks to investigate how to support justice-involved individuals with serious mental illnesses (SMI). In contrast to the more traditional, utilitarian view of care management within a criminal justice context, I argue that this subset of the justice-involved population deserves respectful care and should be recognized as a group of vulnerable individuals. Having conducted a literature review of existing de-stigmatization practices, I recommend ways this population can be supported in removing the dual self-stigma of having a mental illness and criminal record. The intersectionality of these identities should be acknowledged in order to provide the most relevant recommendations to this group, return autonomy, and improve self-efficacy.

Degree:
BS (Bachelor of Science)
Keywords:
Self-stigma, Mental Health, Criminal Justice
Sponsoring Agency:
Jefferson Area Community Criminal Justice Board
Notes:

School of Engineering and Applied Science

Bachelor of Science in Systems Engineering

Technical Advisors: L. Peter Alonzi III, Michael Smith & K. Preston White

STS Advisor: Pedro Francisco

Technical Team Members: Joshua Dornfeld, Livia Hughes, Sarah Murphy, Ronica Peraka & McBride Rawson

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2023/05/11