CANADIAN REFLECTIONS ON THE TOBACCO WARS: SOME UNINTENDED CONSEQUE5NCES OF MASS TORT LITIGATION
Bibliographic record
Abstract
During the 1990s many Commonwealth legislatures enacted ‘class action’ or ‘representative proceedings’ legislation.1The main justification for these initiatives was to increase access to justice for claimants particularly where the injury was widespread but the harm suffered by any particular individual was small. Much of this legislation built on developments in the United States, which had developed a sizable jurisprudence in the area. ‘Mass torts’, those defined as having a large impact engaging multiple claimants, have often formed the cause of action in US class actions. A review of the website ‘Big Class Actions‘,2which lists over one hundred current suits in the United States, is instructive on how the class action industry has grown in that country.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.042 | 0.025 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".