Courting Confusion? Three Recent Alberta Cases on Equality Rights Post-Kapp
Bibliographic record
Abstract
This article examines current confusion surrounding how courts are to analyze challenges brought under s. 15 of the Canadian Charter of Rights and Freedoms. The authors begin with a review of the 2008 Supreme Court of Canada decision in R. v. Kapp, which gave s. 15(2) independent status to shield ameliorative laws, programs, and activities from the finding of discrimination, but left the application of s. 15(1) unclear. The authors then articulate how three recent Alberta cases on equality post-Kapp illustrate the new uncertainty surrounding how courts are to address equality rights. Through an analysis of the Supreme Court’s 2009 decision in Ermineskin Band and Nation v. Canada, and subsequent decisions of the Alberta Court of Appeal in Morrow v. Zhang and Cunningham v. Alberta (Aboriginal Affairs and Northern Development), this article explores the Supreme Court’s failure to adequately guide lower courts and tribunals on how to apply s. 15 post-Kapp. For example, a framework for reconciling the new role of s. 15(2) and claims of under-inclusive ameliorative programs has yet to be developed. Further, the authors argue that the guidance that has been delivered has improperly narrowed the definition of discrimination to stereotyping and prejudice.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".