Bibliographic record
Abstract
Abstract: This paper examines the novel concept of class arbitration in Canada. Given the current fragmented, provincial class actions regime, plaintiffs and defendants face significant barriers in obtaining justice. These obstacles have been compounded by the increase in interprovincial and international class actions. In particular, there are constitutional uncertainties surrounding the certification of national opt-out class actions by provincial superior courts. Moreover, defendants struggle to enforce multijurisdictional class action judgments. Not only does this prevent them from obtaining res judicata, it further reduces judicial economy. Correspondingly, plaintiffs may not be certain whether they are bound by class judgments awarded in other jurisdictions and may have to bring fresh proceedings to recover damages. These challenges undermine the already dire access to justice situation in Canada. This paper argues that class arbitration can address all of these challenges and effectively resolve privacy law disputes, an increasingly litigated area. Notwithstanding these benefits, class arbitration must overcome several hurdles in order to flourish, such as consumer protection legislation and the protection of absent class members’ interests. This paper suggests that class arbitration can overcome judicial opposition to pre-dispute mandatory arbitration clauses, rely upon existing arbitral rules, and protect absent class members’ interests through a combination of high arbitral standards and a system of private enforcement. It therefore argues that class arbitration can and should be embraced in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".