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Record W4391829132 · doi:10.7202/1108775ar

Expériences de (non-)signalement des violences sexuelles en milieu universitaire : des parcours minés et des issues mitigées1

2024· article· fr· W4391829132 on OpenAlexvenueno aff
Manon Bergeron, Ihssane Fethi, Karine Baril, Sandrine Ricci, Jacinthe Dion, Marie-Hélène Ouellette, Geneviève Paquette, T. Paul, Marie-Andrée Pelland, Anne-Sophie Ponsot, Lise Savoie, Cindy Viau

Bibliographic record

VenueRecherches féministes · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Malgré leur prévalence élevée, les violences sexuelles en milieu universitaire demeurent largement sous-signalées. Dans cet article, les auteures décrivent les motifs de (non-)signalement des personnes victimes, et pour celles qui ont signalé la situation, la réponse institutionnelle et les suites de la démarche. L’analyse qualitative de 197 récits révèle le rôle de plusieurs enjeux. Le fait de signaler ou non l’acte de violence sexuelle peut découler d’un sentiment de crainte pour soi et les autres, d’une évaluation des coûts et des bénéfices, et est influencé par un processus de normalisation de la violence. Les rapports inégaux de pouvoir au sein de l’université ajoutent des contraintes supplémentaires au signalement. Ces résultats soutiennent la nécessité de poursuivre le développement de formations obligatoires et de diffusion de messages de sensibilisation qui pourraient améliorer la confiance des personnes victimes envers les établissements.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.006
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.104
GPT teacher head0.402
Teacher spread0.299 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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