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Record W140134012 · doi:10.22329/wyaj.v28i1.4492

Judging Fairness in Class Action Settlements

2010· article· en· W140134012 on OpenAlexaffvenue
Catherine Piché

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsClass actionSettlement (finance)Human settlementContext (archaeology)Action (physics)Class (philosophy)Political scienceCivil procedureDoctrineFace (sociological concept)Economic JusticeLawLaw and economicsSociologyBusinessHistoryEpistemologyState (computer science)Social scienceComputer science

Abstract

fetched live from OpenAlex

In this paper, I describe the face of modern civil justice and discuss four paradoxes which justify re-evaluating the role of the judge responsible for reviewing class action settlements, in light of modern judicial culture. I also critically evaluate the existing procedures applicable to the fairness review as well as the judicial role described in the caselaw and doctrine, before suggesting a revised, three-parted role for the reviewing judge in the class action settlement context. Ultimately, I suggest that to reach fairness of process and outcome in class action settlements, judges should remain active and creative in their inquisitorial assessment of proposed class action settlements. They should also remain conciliatory, participating in the search for solutions regarding the proposed settlement, always seeking to find the truth (and what is “just”) about the proposed settlement, in the utmost respect for the rights of absent class members, the respect of their interests, and the additional consideration of the interests of the defendants and of the public.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2010
Admission routes2
Has abstractyes

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