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“Driving wedges” and “hijacking” Pride

2020· article· en· W3108218298 on OpenAlexaffabout
Andrew Tompkins

Bibliographic record

VenueOñati Socio-legal Series · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsYork University
Fundersnot available
KeywordsThe ImaginaryQueerGender studiesRacismHumanitiesPoliticsSociologyPrideMainstreamMedia studiesPolitical scienceArtLawPsychoanalysis

Abstract

fetched live from OpenAlex

This paper analyzes public debate pertaining to a demonstration by the Toronto chapter of Black Lives Matter (BLMTO) at the city’s 2016 Pride parade. The movement’s actions, and ultimately the organization itself, have been widely condemned for disrupting the event and calling attention to anti-Black racism within the Toronto Police Service and queer spaces. A critical discourse analysis of mainstream media content reveals the emergence of three major themes repeated across Canadian news outlets in the denouncement of BLMTO. Central to this process is the myth of multiculturalism, which effectively displaces the phenomenon of racism onto previous centuries and other countries. By scrutinizing the parameters of the Canadian national imaginary, this paper reveals the ways in which anti-Black racism has become compounded by the mainstream LGBT movement.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.249
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0210.061
Scholarly communication0.0100.004
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.283
Teacher spread0.261 · 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 designQualitative
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

Citations2
Published2020
Admission routes2
Has abstractyes

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