Constitutional Treatment of Hate Speech and Freedom of Expression: a Canada – U.S. perspective
Bibliographic record
Abstract
The present article explores the constitutional treatment of hate speech in Canadian and American law vis-à-vis the paramount place freedom of expression occupies in both legal systems1. The author first pronounces on the conceptional divergence of the freedom, opining that American free speech has retained much of its status as a preferred freedom given its unique historical fomenting process and predilection toward a quasi-absolutist interpretation of the First Amendment. Canada, however, has explicitly declined to institute a hierarchical approach of rights, thus effectively creating a level-playing field through an egalitarian-driven perception of rights when they are in collision. The argument continues by looking into major jurisprudential developments of hate speech in the two respective constitutional orders. Identifying one of the principal legal basis for Canadian courts to strike down constitutional challenges raised in hate speech cases to be strongly grounded in the communitarian understanding of the harm inflicted by hate speech, the observation hints at the distinctively Canadian legal attitude’s overture toward special group rights, multiculturalism, or grosso modo – the promotion of pluralism. The American courts, however, have been reluctant in suppressing speech activity by confiding in a set of extremely narrowly tailored tests to justify constitutional infringements of free speech.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.028 | 0.036 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".