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Record W4413244041 · doi:10.3138/ccar.v15i1.111

Class Actions and Beauty Pageants: The Need for Carriage Motion Reform in Ontario

2019· article· en· W4413244041 on OpenAlexaboutno aff
Cole Pizzo

Bibliographic record

VenueCanadian Class Action Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsCarriageArbitrarinessClass (philosophy)LawPrejudice (legal term)Law and economicsOpt-outPolitical scienceSociologyComputer scienceBusinessAdvertisingEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract: In Ontario, carriage motions have been embraced as the designated method for determining which of competing class counsel will exclusively represent the class. Despite the foundational objective of judicial economy, carriage motions persist as inefficient and deeply flawed procedures. Since the initial factors for the court to consider were enumerated in Vitapharm, the test has grown into a lengthy list of factors which are neither mandatory nor exhaustive. This promotes uncertainty and does little to foster judicial economy or serve the best interests of the putative class. I argue that carriage motions have developed in an unfeasible direction. They encourage wasted resources and effort, create delay in an already lengthy process, and may ultimately prejudice the class. In search of an alternative, I employ a multijurisdictional analysis. The approach of the Federal Court of Australia in resolving competing actions is considered, as is the post-Schmidt approach of Quebec. Embracing the modified first-to-file rule of Quebec is the appropriate direction for carriage motion reform in Ontario. Quebec’s approach balances concerns over the complexity, uncertainty, and potential prejudice of carriage motions with concerns over the arbitrariness and unfairness of a conventional first-to-file rule. This would avoid the lengthy comparative analysis of carriage motions while still serving the best interests of class members.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.052
GPT teacher head0.262
Teacher spread0.210 · 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.

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
Published2019
Admission routes1
Has abstractyes

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