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Extreme Speech and Democracy

2009· book· en· W1488413727 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsIncitementDignityConstitutionalityHatredDemocracySupreme courtLawRacismIdeologyPolitical scienceTerrorismXenophobiaSociologyPolitics

Abstract

fetched live from OpenAlex

Abstract A commitment to free speech is a fundamental precept of all liberal democracies. However, democracies differ significantly when addressing the permissibility of laws regulating certain kinds of speech, especially extreme speech. In the United States, for instance, the commitment to free speech has been held by the Supreme Court to protect the public expression of even the most noxious racist ideology. In contrast, in almost every other democracy governments enjoy considerable leeway to restrict racist and other types of extreme expression. What accounts for the marked differences in attitude towards the constitutionality of hate speech regulation? Does hate speech regulation violate the core free speech principle constitutive of democracy? Or do values such as the commitment to equality or individual dignity legitimately override the right to free speech in some circumstances? In attempting to answer these and other questions, this book focuses on highly topical issues such as homophobic speech, Holocaust denial, incitement to terrorism, veiling controversies, and the Danish cartoons depicting the Prophet Muhammad. It includes interdisciplinary perspectives from law, philosophy, history, psychology, and literature, and provides comparative perspectives from experts in various countries including Australia, Canada, France, Germany, Hungary, and Israel, as well as from the United States and the United Kingdom.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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
GenreOther

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

Citations258
Published2009
Admission routes1
Has abstractyes

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