Contracting Out of Access to Justice: Enforcement of Forum Selection Clauses in Consumer Contracts
Bibliographic record
Abstract
Forum selection agreements by default nominate the business’s home jurisdiction to resolve disputes and thus directly impact a consumer’s ability not only to access courts but to obtain access to substantive justice. It has been argued that the courts should evaluate 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 (excluding Quebec) between 1995 and 2016. The analysis of the surveyed cases shows that the courts have failed to exercise the greater scrutiny that has been 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 dynamic 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 that would invalidate forum selection clauses in consumer agreements and reframing and recalibrating the common law strong cause test for the enforcement of forum selection clauses for consumer transactions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".