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Record W2963838776 · doi:10.3917/cdge.066.0129

Enquêtes nord-américaines sur les violences homophobes et transphobes en contexte scolaire : l’invisibilisation du sexisme

2019· article· fr· W2963838776 on OpenAlexaffabout
Line Chamberland

Bibliographic record

VenueCahiers du Genre · 2019
Typearticle
Languagefr
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article propose une lecture critique de trois enquêtes réalisées respectivement au Canada anglais, au Québec et aux États-Unis, sur le climat scolaire et les violences interpersonnelles entre pairs fondées sur la non-conformité aux normes sexuelles et de genre, dans le milieu scolaire. Il relève l’ampleur de ces violences, qui peuvent toucher tous les élèves, ainsi que la victimisation relativement plus importante des jeunes trans ou non cisgenres et des élèves dont l’expression de genre est non conforme aux normes de genre. Toutefois, ces enquêtes mettent au second plan l’analyse des violences sexistes ou subies en tant que filles, y compris par les filles non hétérosexuelles, de même que l’examen des auteur·e·s des violences interpersonnelles. Tout en constatant l’enchevêtrement et le caractère systémique des violences liées à la sexualité et au genre, ces études négligent de considérer l’asymétrie entre filles et garçons et le rôle des violences interpersonnelles dans la reproduction des rapports sociaux de sexe.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0310.031
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0020.005
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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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 designObservational
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

Citations4
Published2019
Admission routes2
Has abstractyes

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