Prison Misconduct and the Use of Alternative Resolutions by Correctional Officers in Therapeutic Communities and Other Custody Units
Bibliographic record
Abstract
This mixed methods study uses official records and interviews with inmates and staff to compare misconduct in therapeutic communities (TC's) and the use of alternative resolutions (in lieu of formal charges by correctional officers) to other prison units. Prisoner misconduct has been studied using individual self-reports or aggregate prison rates, but unit level differences between TC's and other prison wings are often overlooked. Restorative justice and diversion approaches are much studied in the community corrections literature but correctional officer use of alternatives to charging, such as mediation, is not well understood. The study examines differences in prisoner behavior by unit function by comparing misconduct over a 24 month period in therapeutic communities to general population, worker, protective custody, mental health, and high risk units. Study findings show lower misconduct in TC's, including more serious misconduct such as fights. Furthermore, a significant proportion of overall charges were diverted into alternative resolution (AR)s, particularly within therapeutic communities. Interviewees reported a different approach taken in the TC toward discipline with a greater use of interaction, informal warnings, and application of AR, as opposed to formal charges. Future research is recommended using qualitative research strategies to appraise the alternative resolution decision process and prisoner-staff perceptions of discipline.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".