L'exemple québécois de la Cour des petites créances : « cour du peuple » ou tribunal de recouvrement ?
Bibliographic record
Abstract
La division des petites créances de la Cour du Québec, chambre civile, communément désignée par l'expression « Cour des petites créances », a été instituée en 1971 dans un mouvement général d'élargissement de l'accès des citoyens à la justice. Près de 25 ans plus tard, cette juridiction atteint-elle l'objectif que le législateur de l'époque s'était fixé, notamment au regard d'une catégorie d'usagers particulièrement en quête de justice, les consommateurs ? Les récentes modifications de sa compétence et de ses attributions en 1993 et en 1995, elles aussi présentées dans un courant de réforme de la justice, portent-elles atteinte à sa mission d'origine ? Telles sont les questions fondamentales soulevées dans la présente étude et auxquelles l'auteur tente de répondre.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".