Evaluating an Expedited Process to Assess Fitness to Stand Trial in Canada
Bibliographic record
Abstract
In this study, we investigated the potential benefits of using an alternative approach for completing court ordered fitness to stand trial assessments in a Canadian forensic mental health service. Using file information, court databases, and an economic analysis, we compared a hospital-based model of evaluation to a court clinic model in a sample of 96 accused persons from 2013 to 2017. Results revealed a significantly shorter time period for forensic report completion in the court clinic group, but no difference in criminal case processing time between groups. There was a higher rate of accused persons opined to be unfit to stand trial in the court clinic group (25.9%) compared to the hospital-based model (7.7%). Report quality varied somewhat between groups, with forensic assessment reports citing mental disorder and relevant case law more often in the court clinic model. Economic analyses indicated there was a marked cost savings associated with completing assessments at court instead of hospital. Our findings suggest there are several benefits for forensic mental health systems in utilizing community-based models of forensic evaluation.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".