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Record W4253863679 · doi:10.3138/utlj.2016.0001

Decomposing <i>Bhasin v Hrynew</i>  : Towards an institutional understanding of the general organizing principle of good faith in contractual performance

2017· article· en· W4253863679 on OpenAlexaffvenueabout
Daniele Bertolini

Bibliographic record

VenueUniversity of Toronto Law Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDoctrineLawSupreme courtFaithPolitical scienceCommon lawFair dealingSubject (documents)Function (biology)Law and economicsSociologyGood faithEpistemologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

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.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score0.782

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0090.045
Scholarly communication0.0140.010
Open science0.0030.006
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.298
Teacher spread0.255 · 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 designNot applicable
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

Citations1
Published2017
Admission routes3
Has abstractyes

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