Explicating Alcohol???s Role in Acquaintance Sexual Assault: Complementary Perspectives and Convergent Findings
Bibliographic record
Abstract
This article summarizes the proceedings of a symposium presented at the 2004 meeting of the Research Society on Alcoholism (RSA) in Vancouver, British Columbia, Canada. There were four presentations and a discussant. The symposium was co-chaired by Tina Zawacki and Jeanette Norris. The first presentation was made by Jeanette Norris, who found that alcohol consumption and preexisting alcohol expectancies affected women's hypothetical responses to a vignette depicting acquaintance sexual aggression. The second presentation was made by Joel Martell, who reported that alcohol-induced impairment of executive cognitive functioning mediated the effect of intoxication on men's perceptions of a sexual assault vignette. In the third presentation, Antonia Abbey found that the experiences of women whose sexual assault involved intoxication or force were more negative than were the experiences of women whose sexual assault involved verbal coercion. The fourth presentation was made by Tina Zawacki, who reported that men who perpetrated sexual assault only in adolescence differed from men who continued perpetration into adulthood in terms of their drinking patterns and attitudes toward women. William H. George discussed these findings in terms of their implications for theory development and prevention programming.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".