MétaCan
Menu
Back to cohort
Record W4413244052 · doi:10.3138/ccar.v14i2.279

Assessing Fees when Class Actions Follow Government Action

2019· article· en· W4413244052 on OpenAlexaboutno aff
Misha Boutilier

Bibliographic record

VenueCanadian Class Action Review · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsnot available
Fundersnot available
KeywordsClass actionPlaintiffGovernment (linguistics)EnforcementSupreme courtClass (philosophy)Economic JusticeAction (physics)LawLaw and economicsPolitical scienceBusinessEconomicsComputer science

Abstract

fetched live from OpenAlex

Abstract: The Supreme Court of Canada’s Sun-Rype and Fischer decisions have recently focused attention on the relationship between public enforcement and private class actions. This essay considers an under-studied aspect of that relationship; namely, how courts should calculate fees in a class action that follows and benefits from a prior government enforcement action. The author contends that class actions that follow government actions are less risky for class counsel and are inferior to independently initiated class actions at ensuring behaviour modification and access to justice. Accordingly, the author argues that Canadian courts should follow the US Courts of Appeals for the Second and Third Circuits and adopt a specific rule governing fees when class actions follow government action. This rule would both reward plaintiffs’ attorneys who independently initiate class actions with increased fees, and would reduce fees for class actions that follow government action in proportion to the benefit that class counsel receive from the prior government action. This rule will allow courts to appropriately assess risk in light of the reduced-risk profile that class actions that follow government action generally present. It will also encourage independently initiated class actions and thus help ensure behaviour modification and access to justice for wrongs in cases of government inaction.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.321
Threshold uncertainty score0.646

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.003
Science and technology studies0.0030.003
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.108
GPT teacher head0.278
Teacher spread0.170 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Class Action ReviewSame topicLaw, Economics, and Judicial SystemsFrench-language works237,207