Preventing Suicide in Prisons, Part II
Bibliographic record
Abstract
The International Association for Suicide Prevention created a Task Force on Suicide in Prisons to better disseminate the information in this domain. One of its objectives was to summarize suicide-prevention activities in the prison systems. This study of the Task Force uncovered many differences between countries, although mental health professionals remain central in all suicide prevention activities. Inmate peer-support and correctional officers also play critical roles in suicide prevention but there is great variation in the involvement of outside community workers. These differences could be explained by the availability of resources, by the structure of the correctional and community services, but mainly by the different paradigms about suicide prevention. While there is a common and traditional paradigm that suicide prevention services are mainly offered to individuals by mental health services, correctional systems differ in the way they include (or not) other partners of suicide prevention: correctional officers, other employees, peer inmates, chaplains/priests, and community workers. Circumstances, history, and national cultures may explain such diversity but they might also depend on the basic way we think about suicide prevention at both individual and environmental levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".