Bibliographic record
Abstract
In this article, the author advocates a group-based approach to analysis under section 15 of the Canadian Charter of Rights and Freedoms. Such an approach was first presented by L'Heureux-Dube J. in Egan v Canada. There, L'Heureux-Dube J. argued that the emphasis on enumerated and analogous grounds on equality jurisprudence detracts from a more “effects” or “impact”-based assessment of discrimination. L'Heureux-Dube J. Relinquished her position in the later Supreme Court of Canada decision Law v Canada (Minister of Employment and Immigration), where the unanimous Court retained the requirement that differential treatment be based on one of the enumerated or analogous grounds in section 15. The Law decision, which at the time represented a compromise to different approaches to section 15, has badly fractured in recent equality decisions (Lavoie v Canada and Gosselin v Quebec (A.G.)). The author argues that reconsideration of L'Heureux-Dube J.'s group-based focus in Egan will address some of the weaknesses in the Law framework that have lead to its demise. Through an examination of both the Supreme Court's decision in Trociuk v British Columbia (A.G.) and the Ontario Court of Appeal's decision in Falkiner v Ontario (Ministry of Community and Social Services) (which is slated to be heard by the Supreme Court in 2004), the author supports L'Heureux-Dube J.'s Egan framework as a more meaningful way to consider equality claims. In particular, the author argues that such a group-based approach allows for a more sophisticated understanding of gender equality challenges and offers the courts an easier methodology for assessing claims of complex discrimination.
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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 | 0.052 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.032 |
| Scholarly communication | 0.021 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.005 | 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".