Negotiating the contours of unlawful hate speech: regulation under provincial human rights laws in Canada
Bibliographic record
Abstract
Academic writing and media commentary on Canadian hate speech laws has focused heavily on the offences created by the Criminal Code and the restrictions in the Canadian Human Rights Act on telephonic communication of hate messages. In both cases, this intensity of interest has been prompted by a range of factors including the national operation of these laws, their mobilization against well-known and attention seeking racist organisations and individuals, and the fact that the Supreme Court of Canada has been called upon to rule on the constitutional validity and interpretation of both federal statutes. Consequently, there is a substantial body of academic writing on the decisions of the Supreme Court of Canada in R v. Keegstra and Taylor v. Canadian Human Rights Commission, focusing on the Court’s resolution of the tension between the protection afforded to freedom of expression under the Canadian Charter of Rights and Freedoms and the criminalization of hate speech under the Criminal Code. Comparatively little attention has been devoted to the operation of restrictions on various forms of hate speech contained in the human rights statutes of almost all Canadian provinces and territories. And yet, provincial hate speech laws have a long history in Canada and have been invoked on a number of occasions in efforts to restrict and/or sanction conduct by individuals or groups that promotes ill-feeling and discrimination towards particular minorities, including Jews, Aboriginal people, people of colour, and gays and lesbians.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".