Bibliographic record
Abstract
Similar to cy près distributions in common law Canada and the United States, Quebec courts distribute the balances of damages in class actions to third party charity organizations. This is a crucial step in the class action procedure as it is the judge's final opportunity to protect absent class members’ rights by ensuring that these distributions serve class members’ interests. Despite the frequncy of this practice, the Quebec jurisprudence has not developed a consistent approach to choosing recipients, and judges rarely provide written reasons on the issue. This makes it difficult for absent class members to understand how distributions serve their interests and, in some circumstances, could even create the perception that litigation actors put their own interests ahead of those of the class. This paper provides an empirical survey of balance distributions in Quebec, and emphasizes the importance of providing written reasons for choosing recipients, in order to demonstrate how a distribution specifically serves class members’ interests and to develop a consistent approach to choosing distribution recipients. Such an approach should consider the interests of the class members as well as the objectives of the class action: access to justice, behaviour modification, and judicial economy. The approach should also minimize settlements with fixed third party distributions, ensure that recipients are unrelated to the litigation actors, and aim to distribute funds to specific projects or services that may serve class members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".