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Record W7128239449 · doi:10.3138/ccar.v9i2.271

Paving the Way for Overtime Class Actions

2014· article· en· W7128239449 on OpenAlexaboutno aff
Elba Bendo

Bibliographic record

VenueCanadian Class Action Review · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationOvertimeLegislationClass (philosophy)AppealSet (abstract data type)

Abstract

fetched live from OpenAlex

In June 2012, the Ontario Court of Appeal released three decisions regarding the certification of overtime class actions. In each of the three cases, the court revisits the application of the certification test set out in section 5 of the Class Proceedings Act. By reviewing the court’s judgments, this article aims to develop a framework that can be used to enable the certification of overtime class actions. The Ontario Class Proceedings Act was enacted twenty years ago, yet it remains disputable whether the legislation has achieved its intended benefits. Few cases have passed the high certification hurdle and even fewer have been resolved through post-trial judgments. If class actions are ever to become a viable forum for enforcing workers’ rights, courts must strictly observe and vigorously employ the principles established in the overtime trilogy. Ontario is ready for full-fledged class proceedings; it is now up to the judiciary to give the province’s class actions legislation the generous application it deserves.

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)0.022
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.159
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.051
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0140.010
Scholarly communication0.0120.004
Open science0.0050.004
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0100.002

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 head0.057
GPT teacher head0.284
Teacher spread0.226 · 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 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
Published2014
Admission routes1
Has abstractyes

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