The paramount consideration : decision-making by the British Columbia Review Board in initial disposition decisions
Bibliographic record
Abstract
Within Canadian criminal law, the mental disorder defence grants exemptions from criminal liability to those who commit criminal acts while suffering from a mental disorder that renders “the person incapable of appreciating the nature and quality of the act or omission or of knowing that it was wrong.” Unlike traditional defences, the mental disorder defence does not result in an outright acquittal and unconditional release. Instead, those who satisfy the requirements of the defence are found “not criminally responsible on account of mental disorder” (NCRMD) and become subject to the jurisdiction of a provincial Review Board, which is tasked with reviewing the case of each NCRMD accused annually and deciding whether each accused should be discharged absolutely, discharged with conditions, or detained in a hospital for the purpose of treatment. The Review Board also has jurisdiction over those found unfit to stand trial, but these accused are outside the scope of this thesis. This thesis examines decision-making by the British Columbia Review Board in initial disposition decisions relating to NCRMD accused in 2015 and 2016. A quantitative analysis suggests that the best predictors of disposition in these cases are the sex, age, and diagnosis of the accused. A review of the contents of the Review Board’s decisions confirms the importance of the accused’s mental health status, but also reveals a concern for the accused’s criminal history and ongoing substance abuse. The Review Board is highly focused on risk assessment and the protection of the public to the exclusion of other considerations, including those listed in the governing legislation. This thesis examines this focus on public safety and calls for the introduction of measures to better balance the interest of the NCR accused with those of the public. It concludes with a discussion of the implications of this focus on public safety and calls for the introduction of measures to better balance the interests of the accused with those of the public.
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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 | 0.280 | 0.510 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.034 | 0.008 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".