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Record W4392384628 · doi:10.1177/15570851241236739

“She Should be Smart Enough To Know, Hey, These Things Can Happen”: Identifying Men’s Perceptions, Attitudes and Beliefs About Sexual Aggression Toward Women in Drinking Venues and The Implications for Prevention

2024· article· en· W4392384628 on OpenAlexafffund
Kathryn Graham, Sharon Bernards, Antonia Abbey, Victoria L. Banyard, Peter Donnelly, Tara M. Dumas, Sarah McMahon, Charlene Y. Senn, Kevin M. Swartout, AnnaLise Trudell, Samantha Wells

Bibliographic record

VenueFeminist Criminology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsPublic Health OntarioUniversity of TorontoWestern UniversityUniversity of WindsorCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsAggressionPerceptionPsychologyComputer securityInjury preventionSuicide preventionSocial psychologyHuman factors and ergonomicsApplied psychologyPoison controlMedical emergencyMedicineComputer science

Abstract

fetched live from OpenAlex

Sexual aggression (SA) by men toward women, including harassment and unwanted sexual touching, is ubiquitous in drinking venues. Focus groups with 38 male volunteers aged 19-26 were used to articulate men’s perceptions, attitudes, and beliefs (PABs) related to SA in drinking venues for future development of a comprehensive questionnaire. Three cross-cutting themes relevant to prevention emerged from discussions structured using a 6-dimensional theoretical model: drinking venues culture with normative acceptance of SA as harmless fun, gender scripts that hold female targets responsible for SA, and alcohol attributions that reduce blame for intoxicated men perpetrators and increase blame for women targets.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

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

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 head0.143
GPT teacher head0.421
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2024
Admission routes2
Has abstractyes

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