Inmates in the Role of the "Wounded Healer": The Virtuous of Peer-to-Peer Programs in Prison
Bibliographic record
Abstract
Researchers in the field of crime desistance have recently focused on the strength-based role of the "wounded healer" or "professional-ex", as exemplified by former addicts and prisoners who desist from crime and recover through the professional practice of peer mentoring. Studies point to the many benefits inherent in the role of the “wounded healer” for incarcerated people employed in peer-based rehabilitation roles. These benefits can include opportunities to experience accomplishments and an increasing sense of ability and self-worth. Additional benefits include acquiring a new meaning and purpose in life, the development of a new self-identity, increasing feelings of belonging and satisfaction from life, and a stronger commitment to avoid crime. These findings suggest that formerly incarcerated individuals can form positive, pro-social relationships with their peers and serve as positive role models for them. The purpose of the present article is to review the current literature on peer-to-peer programs currently implemented in Western prisons, to establish and expand them, as a means of improving the rehabilitation efforts of present and past prisoners. It is recommended to examine the preservation of their benefits and effectiveness in the long run, both for aid providers and recipients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".