Pathways to Forensic Mental Health Care in Toronto: A Comparison of European, African-Caribbean, and other Ethnoracial Groups in Toronto
Bibliographic record
Abstract
OBJECTIVE: To describe pathways taken to care by a sample of patients in a secure forensic unit who have been found not criminally responsible or unfit to stand trial, and to investigate the pathways taken by patients within 3 ethnoracial subgroups of origin: European, African or Caribbean, and Other. METHOD: Fifty patients from secure forensic units were interviewed using the Encounter Form developed for pathways mapping undertaken in the World Health Organization field trials. Differences in the types of caregivers seen, the total number of caregivers seen, and the time taken to reach forensic psychiatric services were compared across the 3 ethnoracial groupings. RESULTS: Most people committed their index offence after they had already had contact with general mental health services. Few significant differences were observed in the pathways to secure forensic units across the European, African-Caribbean, and Other ethnoracial groups. CONCLUSIONS: These findings suggest that improvements in general mental health services may be a key to decreasing the use of forensic psychiatric services. Further research is required to explore factors that may predict and prevent offending. Larger studies are needed to examine ethnoracial differences in pathways to care.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".