Bibliographic record
Abstract
Abstract: For nearly two years, the COVID-19 pandemic has brought unprecedented disruption to those living in Canada and around the world. To curb its spread and mitigate its impacts, all levels of government have taken drastic measures to limit movement and social gathering. This has prompted plaintiffs to launch class proceedings alleging unjustifiable violations of Charter rights and to claim awards in damages. This paper examines whether these proceedings are likely to be successful, and ultimately determines that they will not. This paper then argues that the status quo which supports this result is defensible and just. To estimate their likelihood of success, this paper first surveys the history of Charter class actions in Canada and then considers several that have emerged from the COVID-19 context. This paper then reviews the certification test, particularly the cause of action, common issues, and preferable procedure stages, and finds that it is reasonable to expect courts to certify at least some of these class actions. However, since these proceedings likely will and should be denied damages, this would in turn reduce the likelihood of future certification at the preferable procedure stage. Specifically, the Supreme Court of Canada outlined in Vancouver (City) v Ward that courts may refrain from granting damage awards where they would frustrate good governance. This is the main barrier to COVID-19 class actions, as liability in damages would dissuade governments from acting in the best interests of Canadians. As a result, courts should not grant these awards.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.025 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 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".