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Record W4391263655 · doi:10.7202/1108911ar

Expressive Freedom and Ethical Responsibility at Canadian Universities

2024· article· en· W4391263655 on OpenAlexaffabout
Katja Thieme

Bibliographic record

VenueAtlantis Critical Studies in Gender Culture & Social Justice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEthical responsibilityAcademic freedomPolitical scienceEngineering ethicsPsychologyPublic relationsLawEngineeringHigher education

Abstract

fetched live from OpenAlex

This article reviews recent government incursions on questions of free speech at universities and colleges in Ontario and Alberta and presents the challenge they pose to university autonomy. Inherent in university autonomy is the possibility—or the obligation—that universities make decisions based on ethical responsibilities that can extend beyond the limits of current law. As a case study of university autonomy in matters of expressive freedom, I highlight events at the University of British Columbia, which leads me to a discussion of how questions of ethical responsibility have been raised particularly in relation to the speech protection of transgender members of the university. A central issue is the need for universities to adjudicate when free speech rights meet related responsibilities with which they can conflict. I detail how, for instance, the invitation of some anti-trans speakers can pose such a conflict and should lead university communities to consider adjusting their responses in extreme cases so as to be able to more autonomously regulate hateful speech beyond applicable law.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.807
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0640.052
Scholarly communication0.0140.005
Open science0.0020.012
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0080.000

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 head0.061
GPT teacher head0.397
Teacher spread0.336 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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