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Record W4361795238 · doi:10.3998/mpub.11442022

In Defense of Free Speech in Universities

2023· book· en· W4361795238 on OpenAlexaboutno aff
Amy Lai

Bibliographic record

VenueUniversity of Michigan Press eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicAcademic Freedom and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsFree speechHarassmentDemocracyPolitical scienceFirst amendmentRelevance (law)Academic freedomFreedom of expressionLawSociologyPoliticsHuman rightsSupreme courtHigher education

Abstract

fetched live from OpenAlex

In this book, Amy Lai examines the current free speech crisis in Western universities. She studies the origin, history, and importance of freedom of speech in the university setting, and addresses the relevance and pitfalls of political correctness and microaggressions on campuses, where laws on harassment, discrimination, and hate speech are already in place, along with other concepts that have gained currency in the free speech debate, including deplatforming, trigger warning, and safe space. Looking at numerous free speech disputes in the United Kingdom, the United States, and Canada, the book argues for the equal application of the free speech principle to all expressions to facilitate respectful debates. All in all, it affirms that the right to free expression is a natural right essential to the pursuit of truth, democratic governance, and self-development, and this right is nowhere more important than in the university.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.016
Scholarly communication0.0110.007
Open science0.0010.004
Research integrity0.0040.005
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 head0.027
GPT teacher head0.245
Teacher spread0.218 · 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 designTheoretical or conceptual
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

Citations3
Published2023
Admission routes1
Has abstractyes

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