L’Emprisonnement avec sursis au Québec : impact de l’arrêt <i>Proulx</i>
Bibliographic record
Abstract
Conditional sentencing, introduced in Canada in 1996 to reduce the practice of incarceration for sentences of less than two years, allows a convicted offender to serve his or her prison sentence in the community. This article presents the descriptive and analytical findings from unpublished, empirical research on conditional sentencing in the province of Quebec. We elaborate on the changes to probation with respect to the Proulx judgment, pronounced in 2000 by the Supreme Court of Canada, and to the management framework for this measure, implemented throughout Quebec in 2001. An analysis of the findings leads to considerable data on the evolution of conditional sentencing with respect to the clientele, the sentences and, most of all, the court-imposed conditions for conditional sentences, particularly house arrest and curfew. The breach of conditions and re-offending by convicted offenders, and the management of these relapses, complete this portrait of the use, the successes, and the failures of conditional sentencing in Quebec. These results enable us to highlight the fact that the Proulx judgment has had an important impact, in Quebec, on the judicial and administrative practices involved in conditional sentencing.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".