Damages for Breach and Interpretation of Jurisdiction Agreements in Common Law Canada
Bibliographic record
Abstract
An important provision often found in international or interprovincial commercial contracts is a jurisdiction agreement. Such a provision is used by the parties to provide them some measure of certainty regarding the forum in which disputes arising under their contract would be settled. In Canada, it is fairly well established that a jurisdiction agreement serves as a basis of jurisdiction and an action brought in breach of such an agreement shall be stayed, unless there is strong cause why it should not be. However, other aspects of the law on jurisdiction agreements are not yet so well established. For example: What principles guide Canadian courts in the interpretation of jurisdiction agreements and how different are these principles from those applied in the case of ordinary contracts? Can a party impeach the enforcement of a foreign judgment on the basis that it was given by a foreign court in breach of a jurisdiction agreement? And, to what extent can the victim of a breach of a jurisdiction agreement bring an action for damages in respect of that specific breach? This article examines these issues. It identifies areas where there are gaps in the existing jurisprudence and issues on which the law is unsettled or underdeveloped. It proffers solutions to those issues and, for this purpose, draws on comparative jurisprudence from other countries, where appropriate.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".