Fair Compensation or Unjustified Temptation to Compromise?: An Empirical Review of Requests for Honorarium Awards in Canadian Class Actions
Bibliographic record
Abstract
Abstract: Every class action requires at least one representative plaintiff to bring the action, perform certain litigation duties, and represent the interests of the class members. If an action results in a successful outcome for the class, courts may award the representative plaintiff an honorarium as recognition for their contributions. The practice of approving honorariums raises significant policy issues, however. On one hand, judges have justified honorariums payments as appropriate compensation for a representative plaintiff’s service on behalf of others. On the other hand, judges are wary of encouraging the hiring of professional plaintiffs and cautious of creating a perceived or real conflict of interest between representative plaintiffs and the absent class members. In this paper, a comprehensive analysis of the role of representative plaintiffs is undertaken to explain the divergent and unpredictable approaches to honorarium requests taken by courts across Canada’s class actions landscape. Based on an empirical review of 116 published decisions from 2010 to March 2021, this paper argues that there should be a less restrictive and more uniform approach to awarding honorariums in accordance with principles of fairness and the critical purpose of enhancing access to justice.
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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 | 0.002 | 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 | 0.001 | 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".