A More Modest Proposal: Bilingual Submissions Made to the Quebec Minister of Justice in the Context of Possible Reforms to the Class Action Regime
Bibliographic record
Abstract
Abstract: In 2019, at the behest of the Quebec Ministry of Justice, Professor Catherine Piché of the Université de Montreal’s Class Actions Lab, a distinguished legal scholar, published a detailed report on the Quebec class action. Among other things, this report addressed proportionality, authorization (certification), and class counsel fees. The following are the bilingual submissions filed by the authors. These submissions suggest reinforcing the court’s ability to stay or dismiss class actions at the pre-authorization stage, buttressing (rather than eliminating) the second criterion of article 575 of the Code of Civil Procedure, rethinking the assessment of risk when awarding counsel fees, and doing away with Quebec’s controversial “first-to-file” rule in favour of an expedited analysis of competing applications for authorization.
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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 | 0.024 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.034 | 0.019 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".