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Record W2544458016 · doi:10.7202/1040051ar

Contracting out of Access to Justice: Enforcement of Forum-Selection Clauses in Consumer Contracts

2017· article· en· W2544458016 on OpenAlexafffundvenueabout
Marina Pavlović

Bibliographic record

VenueMcGill Law Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Contract Law
Canadian institutionsUniversity of Ottawa
FundersFondation pour la recherche juridique
KeywordsJurisdictionRedressScrutinyLegislatureEnforcementForum shoppingBusinessInherent powersSelection (genetic algorithm)Economic JusticeConsumer protectionLaw and economicsIntervention (counseling)LawPolitical scienceEconomicsConstitution

Abstract

fetched live from OpenAlex

Forum-selection agreements in consumer contracts nominate by default the business’s home jurisdiction to resolve disputes and thus directly impact a consumer’s ability not only to access courts, but also to obtain access to substantive justice. It has been argued that courts should consider enforcing jurisdiction clauses in consumer contracts with “greater scrutiny” because of their inherent power imbalance. To examine how the courts approach forum-selection clauses in consumer contracts, this article analyzed all reported consumer cases involving forum-selection agreements in Canadian common law jurisdictions between 1995 and 2016. The analysis of these cases shows that the courts have failed to exercise the greater scrutiny that was called for. In light of the analysis of the surveyed cases, this article argues that the rules for enforcing forum-selection clauses in consumer contracts ought to be recalibrated to reflect the power dynamics of consumer relationships, the ubiquity of standard-form contracts, and their effect on consumers’ ability to obtain redress. This article proposes two suggestions for reform: legislative intervention to invalidate forum-selection clauses in consumer agreements, and reframing and recalibrating the common law strong-cause test for the enforcement of forum-selection clauses in consumer transactions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.110
GPT teacher head0.413
Teacher spread0.303 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2017
Admission routes4
Has abstractyes

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