Obesity as a Covered Disability Under Employment Discrimination Law: An Analysis of Canadian Approaches
Bibliographic record
Abstract
Since the passage of the first anti-discrimination laws in North America, the number of groups or classes protected has slowly expanded. People with disabilities are one of the more recent groups to be covered by such laws. No Canadian human rights statute includes the obese or overweight as a separate designated group. British Columbia is the only jurisdiction in which obesity per se has been found to be a covered disability. All other Canadian jurisdictions that have explicitly addressed the issue require claimants to prove that their obesity is a disabling condition and has an underlying involuntary medical cause. This paper examines the treatment of the obese under the antidiscrimination laws of the Canadian federal and provincial jurisdictions, focusing primarily upon the laws of Ontario. Its central thesis is that despite the reticence of various human rights agencies, there is ample legal basis for including obesity as a covered disability under human rights law.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".