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Record W4283819427 · doi:10.1093/ips/olac004

The Settler Coloniality of Free Speech

2022· article· en· W4283819427 on OpenAlexaboutno aff
Darcy Leigh

Bibliographic record

VenueInternational Political Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic Freedom and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismWhite (mutation)EnlightenmentPoliticsSociologyFree speechPublic sphereIndigenousEmbodied cognitionLawPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Public and scholarly debates surrounding free speech often assume free speech is a public good and/or should be approached as a problem of “drawing the line” between free and regulated or benign and harmful speech. In contrast, this article provides a genealogy of free speech in which liberal freedom of expression has, since its inception, been integral to white supremacist settler colonialism in the United Kingdom and its former settler colonies, the United States, Canada, Australia, and New Zealand. The article argues that, far from a noble struggle against regulation, liberal politics around free speech establish oppositions between white “civilized” speech and its Indigenized racially darkened “others” as well as controlling or silencing Indigenous, Black and/or otherwise racially othered speech across the Anglosphere. The article first traces free speech through two significant moments in its emergence: early European Enlightenment colonial expansion (embodied in John Locke's “toleration”) and 1800s British colonial industrialization (embodied in John Stuart Mill's “marketplace of ideas”). The article then examines how this genealogy informs the contemporary case study of contestation over free speech in universities, showing that engagements with free speech across the political spectrum extend its settler colonial rationality.

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)0.005
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.040
Scholarly communication0.0100.003
Open science0.0010.005
Research integrity0.0010.003
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 head0.030
GPT teacher head0.362
Teacher spread0.332 · 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
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

Citations11
Published2022
Admission routes1
Has abstractyes

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