Twenty Years Later Taylor Still Has It Right: How the Canadian Human Rights Act’s Hate Speech Provision Continues to Contribute to Equality
Bibliographic record
Abstract
In 1990, the Supreme Court of Canada, in Keegstra and Taylor, upheld legislative restrictions on hate propaganda in the Criminal Code and the Canadian Human Rights Act (CHRA) as constitutionally justified limits on freedom of expression. In this article, the author refutes more recent attacks on the CHRA provision (which ultimately culminated in its repeal following publication of this article). She argues that technological, political and economic changes in the past two decades have created conditions ripe for the scapegoating and abuse of vulnerable groups, making human rights remedies for hate propaganda an even more easily justified component of an equality-based response to bigotry, prejudice and hatred than it was when the Supreme Court of Canada penned its decisions. Asserting that this altered social context undercuts the viability of a free market approach to hate propaganda, the article argues in favour of a principled approach that both respects the co-equal importance of the rights to equality and to free expression within the democratic matrix, and rejects the disproportionate exposure of vulnerable groups to harm that is characteristic of a free market approach.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.028 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".