How Does Alcohol Contribute to Sexual Assault? Explanations from Laboratory and Survey Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article summarizes the proceedings of a symposium of the 2001 RSA Meeting in Montreal, Canada. The chair was Antonia Abbey and the organizers were Tina Zawacki and Philip O. Buck. There were four presentations and a discussant. The first presentation was made by Maria Testa whose interviews with sexual assault victims suggest that there may be differences in the characteristics of sexual assaults in which both the victim and perpetrator were using substances as compared to when only the perpetrator was using substances. The second presentation was made by Tina Zawacki whose research found that perpetrators of sexual assaults that involved alcohol were in most ways similar to perpetrators of sexual assaults that did not involve alcohol, although they differed on impulsivity and several alcohol measures. The third presentation was made by Kathleen Parks who described how alcohol consumption affected women's responses to a male confederate's behavior in a simulated bar setting. The fourth presentation was made by Jeanette Norris who found that alcohol and expectancies affected men's self-reported likelihood of acting like a hypothetical sexually aggressive man. Susan E. Martin discussed the implications of these studies and made suggestions for future research.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it