Bibliographic record
Abstract
In the last seven years, Canada has developed a vigorous class action regime.Before outlining that regime, I would like to address the question: "Why have Class Actions?" I. WHY HAVE CLASS ACTIONS?A foundational document in Canada on class actions is the Ontario Law Reform Commission's (OLRC) Report on Class Actions (1982).1 It is an excellent three volume report that bases its recommendation of the introduction of class actions in Ontario on three underlying policy objectives.The first, and most important objective, is to afford greater access to justice.Litigation has become so expensive that claims of modest amounts, and even those of significant amounts, are not economically feasible to pursue on an individual basis.In class action terminology, these are referred to as "individually non-viable claims."There are many more individually non-viable claims in Canada than in the United States for several reasons: (1) Canada has ceilings on damages for pain and suffering in personal injury cases, and relative to awards in the United States, these ceilings are very low; 2 (2) Canadian courts rarely award punitive damages; 3 (3) the vast majority of civil actions
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.066 | 0.018 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.039 | 0.003 |
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".