The Contribution of Judicial Discretion to a Greying Canadian Prison Population
Bibliographic record
Abstract
Growing numbers of older incarcerated offenders raise a number of challenges\nfor Correctional Services Canada (CSC). Without codification, the method for accounting\nfor the relatively advanced age of older offenders before they become the responsibility\nof CSC is through judicial discretion. However, planned federal justice sentencing\nreforms would reduce the ability for judges to use discretion to account for the specific\ncircumstances of older offenders. This raises the question: would sentencing policy\nchanges result in a greater numbers of older offenders being incarcerated thereby\naggravating the current greying of Canadian prisons? Using a sample of judicial\ndecisions from the British Columbian Provincial Court Database, it is determined that\njudges are considering the 'older age' of offenders. Since judges are tempering the\nproblem of prison population aging, the elimination of judicial discretion through\nsentencing policy changes would result in an aggravation of the current problems\nassociated with prison population aging.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".