A Statistical Survey of Canadian Forensic Mental Health Inpatient Programs
Bibliographic record
Abstract
Secure hospital beds are vitally important for the assessment and treatment of mentally disordered accused persons. A forensic mental health system with an adequate level of hospital beds is essential for the courts and review boards to carry out of the mental disorder provisions of the Criminal Code. This article describes the results of a study that examined interprovincial differences in the structure of Canadian forensic mental health FMH inpatient programs. In total, 1523 hospital beds are designated for FMH programs in Canada. Across Canada, less than one (0.61) FMH hospital bed is available for every 10,000 adults in the general population, ranging from 0.37 in Manitoba to 1.08 in Nova Scotia. Interprovincial differences in the staffing and bed occupancy of Canadian FMH inpatient programs are also uncovered. The results of the present study confirm that interprovincial differences in the structure and organization of FMH inpatient programs exist in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".