Decomposing <i>Bhasin v Hrynew</i> : Towards an institutional understanding of the general organizing principle of good faith in contractual performance
Bibliographic record
Abstract
In Bhasin v Hrynew, the Supreme Court of Canada recognized good faith in contractual performance to be a ‘general organizing principle’ of the common law of contract. The true impact of Bhasin on the future development of Canadian contract law remains the subject of considerable debate among legal scholars and practitioners. This article explores Bhasin’s evolutionary impact on the Canadian common law of contract, by providing an institutional understanding of the general organizing principle of good faith in contractual performance. It is contended that Bhasin’s contribution to the common law of contract is institutional rather than substantive – Bhasin fundamentally alters the organization of the sources of contract law by introducing a new law-making mechanism (that is, ‘law-making through good faith’) that is separate from, and potentially supersedes, the traditional doctrine of precedent. To support the central claim that Bhasin’s contribution is institutional rather than substantive, I employ three different kinds of arguments that correspond to three distinct, but closely related, dimensions of the principle of good faith in contractual performance: (a) semantic structure; (b) historical origins; and (c) economic function. Although these three lines of inquiry rest on quite different methodological premises, they converge in supporting the central idea that good faith performance is best understood as an institutional mechanism to allocate law-making power rather than a substantive legal principle.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".