Efficacy of a Sexual Assault Resistance Program for University Women
Bibliographic record
Abstract
BACKGROUND: Young women attending university are at substantial risk for being sexually assaulted, primarily by male acquaintances, but effective strategies to reduce this risk remain elusive. METHODS: We randomly assigned first-year female students at three universities in Canada to the Enhanced Assess, Acknowledge, Act Sexual Assault Resistance program (resistance group) or to a session providing access to brochures on sexual assault, as was common university practice (control group). The resistance program consists of four 3-hour units in which information is provided and skills are taught and practiced, with the goal of being able to assess risk from acquaintances, overcome emotional barriers in acknowledging danger, and engage in effective verbal and physical self-defense. The primary outcome was completed rape, as measured by the Sexual Experiences Survey-Short Form Victimization, during 1 year of follow-up. RESULTS: A total of 451 women were assigned to the resistance group and 442 women to the control group. Of the women assigned to the resistance group, 91% attended at least three of the four units. The 1-year risk of completed rape was significantly lower in the resistance group than in the control group (5.2% vs. 9.8%; relative risk reduction, 46.3% [95% confidence interval, 6.8 to 69.1]; P=0.02). The 1-year risk of attempted rape was also significantly lower in the resistance group (3.4% vs. 9.3%, P<0.001). CONCLUSIONS: A rigorously designed and executed sexual assault resistance program was successful in decreasing the occurrence of rape, attempted rape, and other forms of victimization among first-year university women. (Funded by the Canadian Institutes of Health Research and the University of Windsor; SARE ClinicalTrials.gov number, NCT01338428.).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".