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A MIXED METHODS INVESTIGATION OF PEER MENTORSHIP DURING REENTRY

thesis
posted on 2023-08-04, 09:57 authored by Esther Matthews

Over the past two decades, recidivism rates have remained relatively stable, leading practitioners to explore innovative reentry solutions. One reentry model, based on the concept of peer mentorship, has received renewed attention. Unfortunately, little is known about which characteristics peers should have, which program components are most beneficial to mentees, and what types of benefits mentees derive from these components. This dissertation uses participant observation and semi-structured interviews, and a variety of surveys to better understand this promising reentry mode from a variety of stakeholder perspectives: prison staff, peer mentors, mentees and people in the community. Findings suggest: 1) peer characteristics associated with lived experiences of incarceration and reentry are the most important peer characteristics, 2) mentors are the most valuable component of the peer mentorship program, and 3) mentees benefited the most from advice their mentors could provide about how to deal with stigma and reentry barriers. Peer mentorship remains a promising option for helping people fully assimilate back into society after incarceration, but a variety of implementation challenges and systemic barriers prevent full reintegration.

History

Publisher

ProQuest

Handle

http://hdl.handle.net/1961/auislandora:94916

Committee chair

Robert Johnson

Committee member(s)

TaLisa Carter; Shadd Maruna; Danielle Rudes; Chris Uggen

Degree discipline

Justice, Law, and Criminology

Degree grantor

American University. School of Public Affairs

Degree level

  • Doctoral

Degree name

Ph.D. in Justice, Law, and Criminology, American University, May 2021

Local identifier

auislandora_94916_OBJ.pdf

Media type

application/pdf

Pagination

175 pages

Access statement

Electronic thesis available to American University authorized users only, per author's request.

Call number

Thesis 11153

MMS ID

99186513694004102

Submission ID

11738

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