“Andrà Tutto Bene/ Ça Va Bien Aller”: Critical Impressions of the Collective Access to Justice Provided in the Model European Rules of Civil Procedure from a Quebec Perspective
Bibliographic record
Abstract
Class actions have been on the rise around the world. They have elevated the global consciousness and crystallised the relevance and importance of collective procedures that can be brought in the name of a group of victims with similar or identical harms. In 2020, Europe has unambiguously directed that Member States must offer collective redress mechanisms in the European Rules of Civil Procedure 2020 (ERCP) and a Directive on representative actions for the protection of the collective interests of consumers. By these Rules, a model for national legislatures was provided, along with a set of converging tendencies in civil procedure across Europe. This article provides a critical commentary of the ERCP collective redress regime, from a Canadian class actions standpoint, and particularly, in light of Quebec’s mixed procedural law regime, its “collective action” mechanism, and empirical data collected by the University of Montreal Class Actions Lab over a 25-year period. Precisely, it addresses a few of the main characteristics of access to collective judicial redress and access to collective settlements, and provides in conclusion some comparative thoughts about future implementation and court interpretations of the Rules.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.032 | 0.059 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".