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Record W4365137505 · doi:10.21428/58a8fd3e.366002fd

Who are the women who commit sexual assault?

2023· article· en· W4365137505 on OpenAlexaff
Ingrid Ménard, Alexandre Gauthier, Alexandre Pavy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCommitSexual assaultCriminologyPsychologyMedical emergencySuicide preventionMedicinePoison controlComputer science

Abstract

fetched live from OpenAlex

Who are the women who commit sexual assault? 2 Who are the women who commit sexual assault?Résumé (français): Jusqu'à tout récemment, la simple idée qu'une femme puisse commettre ou favoriser la commission de comportements sexuels coercitifs était tout simplement impensable ; cela va à l'encontre de la croyance populaire selon laquelle la femme est un être fondamentalement bon.Ce n'est que ces dernières années que la recherche a mis en lumière que la délinquance sexuelle n'est pas un phénomène qui soit propre aux hommes, et que les femmes aussi commettent des agressions sexuelles ; parfois, sous la contrainte et, d'autres fois, de leur plein gré ; parfois, en solitaire et, d'autre fois, avec un partenaire.Qui sont donc ces femmes ?C'est à cette question que le présent article de vulgarisation scientifique tente de répondre.Nous commencerons par examiner les grands mythes entourant la délinquance sexuelle des femmes et l'influence qu'ont eue ces derniers sur le taux de prévalence de ce type de délinquance.Nous brosserons ensuite le portrait type de la délinquante sexuelle, tout en explorant les distinctions qui existent entre celles qui agissent seules et celles qui agissent avec un partenaire.Finalement, nous examinerons les paramètres à prendre en considération dans la prise en charge de ces femmes dans un contexte thérapeutique.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.349
Teacher spread0.289 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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