From Edmonds to Campbell: A Principled Basis for Pre-Certification Costs
Bibliographic record
Abstract
Protection against cost awards is a central feature of almost all class action legislation in Canada. The various protections afforded in each jurisdiction appear to be very similar when comparing the legislation from one province to the next; however, judicial approaches to cost awards have been very inconsistent — both within individual jurisdictions and when comparing one to the next. Failure to consistently apply these provisions has led to uncertainty that threatens to undermine the very issue of access to justice that cost protections are aimed to protect. The author undertakes a critical analysis of the historical development of various “no-costs” interpretations in Canadian jurisdictions in order to highlight the differences in approach and in hopes of drawing out an underlying set of principles. The author moves on to adopt the position of the Federal Court with respect to costs in Campbell v Canada, and concludes with an analysis of legislative intent underlying the various class action regimes.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.028 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".