Lost in Translation?: The Disability Perspective in Honda v. Keays and Hydro-Quebec v. Syndicat
Bibliographic record
Abstract
Two recent decisions from the Supreme Court of Canada, Honda Canada Inc. v. Keays and Hydro-Québec v. Syndicat des employé-e-s de techniques professionnelles et de bureau d’Hydro-Québec raise concerns about the extent of human rights protections for employees with disabilities. In this comment the author argues that when disabilities do not fit neatly into a standard medical framework such as the conditions of chronic fatigue syndrome or mental illness, there is a tendency to disbelieve the employee, not take the individual seriously, or set out special regimes for confirmation. With a focus on the employment contract rather than discrimination, the author argues that an analysis of human rights obligations was virtually absent in the employment law context. In the labour law context, the Court gave no real guidance about the meaning of undue hardship. The author suggests that these cases do not reflect the broad vision of an inclusive workplace previously set out in Meiorin.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.036 | 0.033 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.018 | 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".