Gender, Psychiatric Symptomatology, Problem Behaviors and Mental Health Treatment in a Canadian Provincial Correctional Population: Disentangling the Associations between Care and Institutional Control
Bibliographic record
Abstract
Efforts to increase the provision of mental health care for prisoners have been met with criticism suggesting that mental health treatment in prison is likely to serve institutional rather than inmates’ interests. In this context, the present study seeks to explore the use of various forms of mental health treatment with mentally ill offenders as a function of diagnosis, problem behavior in the institution, and gender among a sample of 513 Canadian inmates. The data was obtained from a review of institutional files as well as face-to-face interviews with inmates. Associations between the main variables were examined using multivariate logit analysis. Results indicate that the provision of mental health care in Canadian provincial institutions is still minimal. Furthermore, women inmates are significantly more likely to receive mental health services compared with their male counterparts. Psychiatrists appear to have a particularly important role in managing conduct problems in the institution. Finally, the presence of dysphoria or social withdrawal in inmates is associated with an increased probability of being provided with individual or group therapy. The results suggest that factors other than psychiatric symptomatology, such as gender and institutional misconduct, may influence the provision of mental health care services in correctional settings.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".