Sentencing Neurocognitively Impaired Offenders in Canada
Bibliographic record
Abstract
While there is general agreement that the great majority of offenders who are sentenced to prison live with a mental disorder and/or a neurocognitive impairment, there is a paucity of research that examines the impact of these conditions on sentencing decisions. This article analyses three studies that reviewed Canadian sentencing decisions obtained from legal databases. Specifically, the article examines the extent to which neurocognitive impairment was treated as a mitigating factor. The analysis indicates that psychopathy was considered to be an aggravating factor insofar as it was associated with a lengthy or indeterminate prison sentence. FASD was consistently considered a mitigating factor with respect to young offenders but, for adult offenders, the judicial approach was variable with less concern for a specific diagnosis and treatment. In a small number of adult cases, PTSD was explicitly identified as a mitigating factor in the judgments, but only if it was causally connected to the offence(s). However, in cases involving young offenders, judges were more likely to focus on the need for treatment of this condition and speedy intervention to achieve rehabilitation. ADHD was not given much weight in sentencing decisions involving either young or adult offenders.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".