The Collective Class Action: An Expansion of the Class Action Framework
Bibliographic record
Abstract
Abstract: In the class actions context, Aboriginal rights and Indigenous issues have largely been considered from an individualistic perspective. Indeed, the use of class actions to address violations of collective rights has only been afforded cursory consideration. This paper argues that the class action framework can expand to accommodate collectives seeking remedies for violations of collective rights, constructing a collective class action framework. Three existing mechanisms of the class action framework can be used to ensure collective class actions are efficient, effective, and constructive. First, the potential opt-in configuration of class actions can acknowledge the diversity and autonomy of Indigenous peoples in Canada. Second, the class of collectives can establish an internal governance structure that can assume the role of representative plaintiff. And third, in no-cost regimes, the protection from costs is invaluable to Indigenous litigants, many of whom have finite financial resources. In jurisdictions that allow an award of costs in class proceedings, judges can, and should, use their public interest discretion to not award costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".