The Silence of Section 15: Searching for Equality at the Supreme Court of Canada in 2007
Bibliographic record
Abstract
This paper considers the Supreme Court of Canada’s 2007 section 15 jurisprudence, and analyzes the “year that wasn’t”. The Equality Rights provision was only referred to in four cases, and in each instance the Court’s reasoning was very brief, amounting at best to a handful of paragraphs. While the Supreme Court may have been subdued in its equality rights jurisprudence in 2007, equality-seekers should not ignore what did (or did not) happen in the past year. The author reviews Charkaoui v. Canada (Citizenship and Immigration), Canada (Attorney General) v. Hislop, Health Services and Support-Facilities Subsector Bargaining Assn. v. British Columbia (B.C. Health Services) and Baier v. Alberta, and considers what the Court said about section 15 in each decision, as well as what might have been said. The author concludes that we should be particularly concerned about the decision in B.C. Health Services, for its failure to consider the intersecting oppressions of gender and occupational status results in serious limitations to understanding intersecting grounds of disadvantage. The 2007 cases might have offered a chance to acknowledge unfortunate developments in section 15 methodology and offer some guidance in restoring a vision of section 15 that focuses on substantive equality. Instead, the Court seriously curtailed the potential of equality litigation and further closed the door to advocates and intervenors interested in progressive equality interpretations.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.041 | 0.020 |
| Scholarly communication | 0.024 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.022 | 0.025 |
| 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".