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Record W1605145486 · doi:10.60082/2563-8505.1271

Hate Speech and the Reasonable Supreme Court of Canada

2013· article· en· W1605145486 on OpenAlexaboutno aff
Mark J. Freiman

Bibliographic record

VenueSupreme Court law review · 2013
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsConstitutionalitySupreme courtLawHatredHuman rightsPolitical scienceLegislationCommissionHarmFundamental rightsTribunalSociologyPolitics

Abstract

fetched live from OpenAlex

In Saskatchewan (Human Rights Commission) v. Whatcott, the Supreme Court of Canada unanimously reaffirmed the constitutionality of anti-hate human rights legislation. This paper explores the Court’s reliance on the pragmatic concept of “reasonableness” to narrow the proper scope of such legislation, in particular: when revisiting the definition of “hatred” under the Saskatchewan Human Rights Code; when conceptualizing the “harm” caused by hate speech; when considering minimal impairment under the Oakes analysis; and when articulating the standard of review applicable to human rights tribunals. The author finds that, in all but one of the above areas, the Whatcott Court’s recourse to “reasonableness” is a principled approach to hate speech and to the Court’s own role in regulating expressive freedom. However, the author argues that “reasonableness” is a troubling standard by which to review tribunal decisions on the substantive question of whether specific communications constitute hate speech; this may be one bridge to “reasonableness” too far.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.048
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0270.013
Scholarly communication0.0170.004
Open science0.0030.003
Research integrity0.0140.016
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.011
GPT teacher head0.216
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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