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Record W7128196997 · doi:10.3138/ccar.v8i1.121

“The Sport of Kings”: Financing Class Actions in Ontario

2012· article· en· W7128196997 on OpenAlexaboutno aff
Jean‐Marc Leclerc

Bibliographic record

VenueCanadian Class Action Review · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffSettlement (finance)Class actionStatutory lawClass (philosophy)Certification

Abstract

fetched live from OpenAlex

Class actions can be very expensive. Certification motions are hotly contested. Trials can be long and expensive. In Ontario, at every step of the process, the representative plaintiff (and any law firm that agrees to indemnify the representative plaintiff) can be liable for significant adverse cost awards. For many years, the Class Proceedings Fund (the Fund) was the only option available for plaintiffs requiring financial assistance. In exchange for 10 percent of any settlement or judgment, the Fund would agree to provide funding for disbursements and to be liable for any adverse cost awards. More recently, other options have become available to plaintiffs requiring financial assistance to bring class actions. Third party companies have offered equivalent arrangements to the Fund, at cheaper cost. While the Fund’s assistance is permitted by statute, there is no equivalent statutory framework to regulate third party financing of class actions. The issue potentially engages questions of champerty and maintenance, as well as other issues, including the amount of control the funder should have over the litigation itself. The paper reviews the historical approach to third party funding of class actions in Ontario and the more liberal approach to these arrangements in recent years. It examines how courts in other jurisdictions such as the United Kingdom, the United States, and Australia have sought to regulate and address third party financing of class actions. The paper draws on these approaches to suggest a framework for third party financing of class actions 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.059
GPT teacher head0.270
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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