Bibliographic record
Abstract
This article analyzes when expression is discriminatory and when discriminatory expression should be legally prohibited. It reaches theoretical conclusions about these matters by examining the recent Ward v. Quebec (Commission des droits de la personne et des droits de la jeunesse) judgment of the Supreme Court of Canada. In Ward, the Court determined that a comedian’s jokes that ridiculed the appearance of a disabled boy did not constitute discriminatory expression because of disability. In any event, there was no reason to prohibit them under Quebec’s Charter of Human Rights and Freedoms that could outweigh the countervailing reason to protect the comedian’s freedom of expression. We argue that there are two weaknesses in the Court’s opinion. First, the Court adopted a conception of how to define expression as discriminatory expression that is inconsistent with standard approaches to this issue in law and the philosophical literature on the ethics of antidiscrimination. Second, while the Court held that only the imperative to prevent harm gives a reason to prohibit discriminatory expression, as opposed to preventing offence, it relied on an impoverished conception of harm that was restricted to the societal harm of hate speech. There are reasons to prohibit discriminatory expression to prevent other types of harms.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".