Young women's risk of sexual aggression in bars: The roles of intoxication and peer social status
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Previous research suggests a link between women's drinking and sexual victimisation; however, little is known about other factors that influence risk and how risks are linked to drinking-in-the-event. We examined how amount of alcohol consumed and peer group factors were associated with whether young women were targeted for sexual aggression on a night out at a bar. DESIGN AND METHODS: One hundred and fourteen women recruited in small groups in the bar district reported how many drinks they had consumed and were breath-tested at recruitment and on their way home. At recruitment, they also ranked other members of their group in terms of status (e.g. popularity, group influence). In the exit survey, they reported any sexual aggression they experienced that night (i.e. persistence after refusal and unwanted sexual touching). RESULTS: Over a quarter (28.9%) of women reported persistence only, 5.3% unwanted touching only and 18.7% both. Sexual aggression was associated with consuming more alcohol on the survey night and whether other group members experienced sexual aggression that night. The relationship with amount consumed was stronger for touching than for persistence. Having a lower status position in the group was associated with increased risk of sexual aggression among women who had consumed five or more drinks. DISCUSSION AND CONCLUSIONS: Prevention should address social norms and other factors that encourage men to target specific women for sexual aggression, including perceptions by staff and patrons that intoxicated women are 'easy' or more blameworthy targets and the possible role of women's social status in their peer groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".