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Record W4412623000 · doi:10.7202/1118817ar

« “Engagez-vous”, qu’ils disaient ! »

2023· article· fr· W4412623000 on OpenAlexaffvenue
Sirma Bilge

Bibliographic record

VenueSociologie et sociétés · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Faisant fond sur les perspectives singulières de femmes noires, de couleur ou autochtones, ainsi que sur les recherches de personnes queers de couleur, ce chapitre examine la manière dont les champs des savoirs minoritaires et les personnes qui en sont à l’origine réagissent aux interpellations néolibérales du monde universitaire occidental, notamment à cette nouvelle appétence pour la différence — réduite à une forme de diversité anodine, porteuse de phénomènes toxiques. Cette réflexion s’appuie sur une vision du néolibéralisme comme un vaste projet éducatif ou une pédagogie sociale visant à remodeler la société, y compris nos subjectivités, à l’image de ses propres principes de rationalité et de relationnalité marchandes, une entreprise qui s’étend en absorbant et en neutralisant, dans une certaine mesure, ses propres critiques, notamment celles émanant des projets de savoirs minoritaires et des personnes qui les ont créés. Son intention : participer à l’essor d’une littérature savante consacrée à la définition collective d’autres possibles, d’autres formes de relationnalité et de contre-institutionnalité dans l’université blanche néolibérale.

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)0.007
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.019
Scholarly communication0.0100.008
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0130.003

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 head0.835
GPT teacher head0.663
Teacher spread0.172 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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