Transformations récentes de la législation fédérale sur la mise en liberté sous condition au Canada. Une lecture à la lumière des écrits sur la notion de risque
Bibliographic record
Abstract
Cet article s'intéresse aux tendances de la loi sur la mise en liberté sous condition au Canada depuis le milieu des année 70. Contrairement à la conclusion selon laquelle la mise en liberté sous condition serait victime d'attrition, il est démontré que ce qui anime cette loi est davantage la tendance duale, aussi appelée bifurcation. De plus, il est avancé que cette tendance duale opère de plus en plus sur la base du critère de risque. La démonstration procède par l'examen des transformations du texte de la loi sur la mise en liberté sous condition depuis son implantation en 1899. L'observation des discours officiel et politique qui ont court à deux périodes charnières de cette mesure, 1956-1960 et 1988-1992, permet ensuite de voir comment ces discours stimulent la tendance duale et l'approche de gestion des risques observée dans la loi.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".