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Record W4403415395 · doi:10.26034/la.cfs.2024.4641

Article court: La couverture médiatique des dénonciations d’agressions sexuelles a-t-elle un biais hétéronormatif ?

2024· article· fr· W4403415395 on OpenAlexaffabout
Alexandra Dupuy, Marianne Laplante, Spencer Nault

Bibliographic record

VenueCriminologie Forensique et Sécurité · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à MontréalYork UniversityUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

La neutralité étant attendue dans la rédaction médiatique, la personne qui écrit possède une discrétion éditoriale (Bolton c. La Presse ltée, 2023) ce qui peut résulter en un refl et de certains biais par des traits linguistiques (par exemple Tranchese, 2023). Morrison et al. (2021) ont observé dans un corpus médiatique canadien anglophone que les cas d’agressions sexuelles portant sur des personnes issues des communautés LGBTQIA2S+ étaient plus détaillés et comportaient des passages plus explicites que ceux portant sur des personnes cishétérosexuelles. Dans cette lignée, nous analysons la dimension du genre dans la description médiatique des violences sexuelles queer, plus particulièrement avec les cas d’Éric Salvail et de Maripier Morin. Les analyses révèlent qu’une description plus explicite est eff ectuée dans le cas d’Éric Salvail comparativement à Maripier Morin, que ce soit par le nombre de passages détaillés de l’agression dénoncée ou par la forte présence d’items lexicaux appartenant au champ sémantique des organes sexuels.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.263
GPT teacher head0.456
Teacher spread0.193 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes2
Has abstractyes

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