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Record W134366855

The Evolution of the Class Action Trial in Ontario

2014· article· en· W134366855 on OpenAlexaboutno aff
Jon Foreman, Genevieve Meisenheimer

Bibliographic record

VenueScholarship@Western (Western University) · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsClass actionClass (philosophy)Action (physics)Political scienceMathematicsComputer sciencePhysicsArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Only a few short years ago, there was a nearly universal view among practitioners in the class actions field: any class action case that could be certified was almost surely going to settle. The fact of the matter, however, is that this universal view is incorrect. Full-blown class action trials have been occurring in Canada for decades. The authors of this paper embarked on an investigative research project in 2011, aimed at discovering, to the greatest extent possible, all class action matters across the country that had been tried since the advent of class action legislation. Because there were no sources of consolidated information, the investigation required both conventional and unconventional research techniques. This paper will describe the investigation and its surprising results, suggest techniques for trial management, and conclude that class action proceedings have evolved into a healthy process for trial resolution.

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)0.017
metaresearch head score (Gemma)0.059
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: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.059
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0510.024
Scholarly communication0.0150.004
Open science0.0050.011
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.083
GPT teacher head0.280
Teacher spread0.196 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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