Bibliographic record
Abstract
Ontario’s Class Proceedings Fund (CPF) provides disbursement support for class actions initiated in Ontario. It was established in 1992 as part of Ontario’s class action regime with the goal of increasing access to justice. During the twenty years since it was established, there have been concerns expressed about whether or not it has fulfilled its intended function. Recently, third party funders have entered the marketplace, and some members of the bar have questioned the CPF’s continued relevance. Others have questioned the CPF’s sustainability given increasing costs awards. This article attempts to critically address these issues with reference to the historical data. It argues that the CPF has enhanced class members’ abilities to more fully pursue their lawsuits in Ontario compared to other forms of funding. To date, third party funding has not significantly affected the CPF as third party funders operate in a different market from the CPF; many of the types of cases that the CPF supports are unlikely to attract third party funding. Further, the CPF offers a method of funding that has the least potential for conflicts of interest — an issue that is currently of significant concern with respect to third party funding arrangements. This article concludes by arguing that for the foreseeable future, the CPF will remain sustainable and will continue to be an important part of the class action framework in Ontario.
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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".