Judicial Consideration of us Proceedings in Canadian Class Action Settlement Approvals
Bibliographic record
Abstract
In Canada, class action settlement approvals require that a court find that the settlement is fair and reasonable with respect to the settlement class as a whole. In some instances, due to a lack of factually comparable cases in Canada, but where there is a nearly identical proceeding in the US, the courts will look to the similar US settlement to aid in determining the fairness and reasonableness of the Canadian settlement. Reviewing a selection of judicial decisions regarding Canadian settlement approvals, this article draws some conclusions on the use of American settlements in Canadian approvals. Generally speaking, where the court is satisfied that Canadian counsel were aware of and took into consideration the American settlement and where the Canadian settlement amount is roughly in line, proportionally, to the US settlement, a finding of fairness and reasonableness is more likely.
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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 | 0.042 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".