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Record W7128217306 · doi:10.3138/ccar.v10i1-2.203

Institutional Abuse Class Actions Post- <i>Cloud</i>

2015· article· en· W7128217306 on OpenAlexaboutno aff
Jody Brown

Bibliographic record

VenueCanadian Class Action Review · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsCompensation (psychology)Class (philosophy)Class actionEconomic JusticeCertification

Abstract

fetched live from OpenAlex

The ten-year anniversary of the certification decision in Cloud v Canada (AG) was this year. The successful certification of Cloud heralded a new era of litigation in Ontario that has increased access to justice for thousands of marginalized plaintiffs. Since Cloud, class actions seeking compensation for historical abuse have multiplied in Ontario and flourished. These class actions have sought more than just monetary compensation and have resulted in apologies for historical relationships and historical wrongs. The post-Cloud jurisprudence is an important accomplishment and development for class proceedings in Ontario over the last ten years.

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)0.025
metaresearch head score (Gemma)0.048
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.763

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.048
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0200.012
Scholarly communication0.0090.003
Open science0.0050.004
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.085
GPT teacher head0.287
Teacher spread0.202 · 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
GenreCommentary

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
Published2015
Admission routes1
Has abstractyes

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