Empowerment through education: Sexual assault resistance programs for girls and young women
Bibliographic record
Abstract
Empowerment through education: Sexual assault resistance programs for girls and young women Charlene Y. Senn and Sara E. Crann from the University of Windsor discuss the importance of sexual assault resistance programs in equipping girls and young women with the knowledge and skills to reduce the risk of sexual assault. Sexual assault is a form of gender-based violence. While anyone can be a victim, research consistently finds that victims are most often girls and women (~85%), and 90% of perpetrators are boys and men. Research also shows that it is girls and young women between 14-24 years old who are at the highest risk for sexual assault. Despite over 50 years of high-quality research on sexual assault and widespread attention to the issue through movements like #MeToo, we have seen little progress in reducing sexual assault on a broad scale. Ending sexual assault requires a comprehensive strategy that includes:
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".