Quebec v A and Taypotat: Unpacking the Supreme Court’s Latest Decisions on Section 15 of the Charter
Bibliographic record
Abstract
The Supreme Court of Canada’s articulation for the test for discrimination under section 15 of the Charter has undergone numerous permutations over the past twenty-five years. The Supreme Court introduced its latest round of changes in its 2013 decision in Québec (Attorney General) v A and its 2015 decision in Kahkewistahaw First Nation v Taypotat. Together, these two decisions clarified that the appropriate approach to section 15 was not one focused strictly on stereotype and prejudice, but rather on all contextual factors that may inform whether an impugned law violates the norm of substantive equality. This paper critically analyzes the impact of Québec v A and Taypotat by examining how courts across the country have articulated the doctrinal messages of these two decisions, and applied them in practice. Both quantitative and qualitative analyses are employed. Under the quantitative approach, the likelihood of mounting a successful s. 15 challenge under the new framework set by Québec v A and Taypotat as compared to the prior test from Kapp and Withler is considered. Under the qualitative approach, a number of key questions are asked, including: what the meaning of the Québec v A and Taypotat touchstone for discrimination – “arbitrary disadvantage” – is; what role stereotype and prejudice continue to play as indicia of discrimination; and what other contextual factors courts will examine in assessing whether discrimination has occurred. The author concludes that although the approach under Québec v A and Taypotat requires some fine-tuning, overall it is a positive move toward a less formalistic, less onerous standard for equality claimants that better reflects section 15’s focus on substantive equality.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".