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Record W1986313535 · doi:10.2202/1535-1661.1164

USA-Canada Class Actions: Trading in Procedural Fairness

2005· article· en· W1986313535 on OpenAlexaffabout
Geneviève Saumier

Bibliographic record

VenueGlobal Jurist Advances · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsMcGill University
Fundersnot available
KeywordsClass actionNoticeRes judicataClass (philosophy)Context (archaeology)Political scienceSettlement (finance)JurisprudenceDoctrineLaw and economicsAction (physics)LegislatureLawBusinessEconomicsGeographyComputer scienceFinance

Abstract

fetched live from OpenAlex

The US class action model and experience has influenced Canadian developments in collective litigation such that in recent years there has been a frenzy of legislative activity making class actions available virtually throughout the country. Now that two thirds of NAFTA is a class action zone, few policy obstacles stand in the way of actions covering both markets. For these to be viable, however, preclusive effect against class members in one country must be forthcoming for judgments or settlements rendered in the other country. In the first decision to consider this issue on the Canadian side, an Ontario appellate court held that an Illinois settlement was not binding on absent Canadian class members, on the basis of inadequate notice. Despite this negative conclusion, the judgment heralds a positive future for USA-Canada class actions by declaring a principle of recognition, dependant only on evidence of procedural fairness. This evidence is based on criteria well known to American doctrine and jurisprudence, namely adequacy of notice and of representation. The manner in which these requirements can be met is explored in the article, along with other possible means of enhancing efficiency and fairness in the context of cross-border class actions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.952

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)0.0000.000

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 head0.013
GPT teacher head0.256
Teacher spread0.242 · 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 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
Published2005
Admission routes2
Has abstractyes

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