Report to the Canadian Human Rights Commission Concerning Section 13 of the Canadian Human Rights Act and the Regulation of Hate Speech on the Internet
Bibliographic record
Abstract
In June of this year I was asked by the Canadian Human Rights Commission (CHRC) to consider, and to make recommendations concerning, “the most appropriate mechanisms to address hate messages and more particularly those on the Internet, with specific emphasis on the role of section 13 of the CHRA [Canadian Human Rights Act] and the role of the Commission.”I was asked to “take into consideration: existing statutory/regulatory mechanisms; whether they are appropriate and/or in any manner, require further precision; the mandates of human rights commissions and tribunals, as well as other government institutions presently engaged in addressing hate messages on the Internet; whether other governmental or non-governmental organizations might have a role to play and if so, what that role might be; Canadian human rights principles, including but not limited to, those contained in the Canadian Human Rights Act and the Canadian Charter of Rights and Freedoms; Canada’s international human rights obligations; and comparable international mechanisms.” I was asked to provide a final report to the Commission on or before October 17, 2008.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".