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Record W1606628352

Consumer Dispute Resolution: The Evolving Canadian Landscape

2008· article· en· W1606628352 on OpenAlexaffabout
Geneviève Saumier

Bibliographic record

VenueSSRN Electronic Journal · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsMcGill University
Fundersnot available
KeywordsArbitrationDispute resolutionLegislationDispute mechanismClass actionOnline dispute resolutionAlternative dispute resolutionBusinessLaw and economicsAction (physics)Compulsory arbitrationDiversity (politics)Consumer protectionPolitical scienceLawEconomicsState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

Consumer dispute resolution mechanisms are facing rapidly evolving legal change in Canadian jurisdictions. With the rise in pre-dispute mandatory arbitration clauses in standard form consumer contracts, courts and legislators have intervened to determine the interaction between judicial policies embodied in class action and arbitration regimes, as these apply in the consumer field. The article examines recent case law and legislation that has given priority to class actions over arbitration in consumer disputes and considers the impact of the diversity of approaches in the various provinces, including the transborder issues involved.

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)0.020
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.371
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.020
Science and technology studies0.0360.032
Scholarly communication0.0310.007
Open science0.0070.006
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0180.001

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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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 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
Published2008
Admission routes2
Has abstractyes

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