Peer Support and Well-Being: Exploring the Impact of Peer-Led Induction on Male Prisoners
Bibliographic record
Abstract
Since 1988, the Journal of Prisoners on Prisons (JPP) has been a prisoner written, academically oriented and peer reviewed, non-profit journal, based on the tradition of the penal press. It brings the knowledge produced by prison writers together with academic arguments to enlighten public discourse about the current state of carceral institutions. This is particularly important because with few exceptions, definitions of deviance and constructions of those participating in these defined acts are incompletely created by social scientists, media representatives, politicians and those in the legal community. These analyses most often promote self-serving interests, omit the voices of those most affected, and facilitate repressive and reactionary penal policies and practices. As a result, the JPP attempts to acknowledge the accounts, experiences, and criticisms of the criminalized by providing an educational forum that allows women and men to participate in the development of research that concerns them directly. In an age where `crime` has become lucrative and exploitable, the JPP exists as an important alternate source of information that competes with popularly held stereotypes and misconceptions about those who are currently, or those who have in the past, faced the deprivation of liberty.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".