La judiciarisation criminelle des violences envers les femmes : Vers un droit sensible aux victimes?
Bibliographic record
Abstract
Les violences envers les femmes dont les violences sexuelles, la violence conjugale ou encore l’exploitation sexuelle ne cessent de faire la manchette au Canada. De plus en plus, on demande au système judiciaire d’apporter des solutions afin de contribuer à endiguer ce fléau social. Le présent article s’inscrit dans cette discussion en revenant sur une recherche menée auprès d’une cinquantaine de femmes victimes de violence et en analysant leur perception du système de justice pénale. Cette recherche, rendue publique en 2018, faisait état des principales critiques des femmes à l’égard du système ainsi que de leurs recommandations pour l’améliorer. Notre objectif général sera de voir si le système judiciaire parvient à se renouveler afin de mieux répondre aux attentes de ces victimes.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".