Bhasin v. Hrynew: A New Era For Good Faith in Canadian Employment Law, or Just Tinkering at the Margins?
Bibliographic record
Abstract
In Commonwealth Bank Australia v Barker the High Court of Australia refused to impose an implied duty of mutual trust and confidence into the employment contract, reasoning that doing so would take the Court beyond its legitimate authority.[1] Issued a bare two months later, the Supreme Court of Canada went in a different direction. In Bhasin v. Hrynew, the Court acknowledged good faith as a central organizing principle of contract law, and announced a new duty of honest performance applicable to all contracts. A few months later the Court applied the new organizing principle of good faith to circumscribe the exercise of an employer’s discretion in Potter v. New Brunswick Legal Aid Services Commission.[2] This paper will assess the potential impact of Bhasin and Potter on the shape of Canadian employment law. In particular, it will reflect on whether these two cases open to the door to greater judicial oversight of the day-to-day interactions between employers and employees, an area as yet relatively unregulated by the Canadian common law.\n[1] Commonwealth Bank of Australia v Barker [2014] HCA 32 (10 September 2014) [Barker]\n[2] Bhasin v. Hrynew, 2014 SCC 71 [Bhasin]; Potter v. Legal Aid Services Commission, 2015 SCC 10 [Potter].
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.019 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 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".