Yes, (most) men know what rape is: A mixed-methods investigation into college men’s definitions of rape.
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
Sexual violence, including rape, is a pervasive problem on college campuses in the United States. Although men perpetrate the majority of sexual violence, men's attitudes, experiences, and perspectives are not typically included in research on rape and sexual violence. We addressed this empirical gap through our mixed-methods analysis of 365 college-aged men's definitions of the term "rape." Our analysis via consensual qualitative research revealed that men's definitions fit into nine primary domains: lack of consent, taken advantage of, sex, sexual activity, unwanted, gender/sex-specific, harm to victim, relationship, and emotional response, as well as a miscellaneous domain. Further, using chi-square tests of independence, we compared responses from men with and without histories of sexual violence perpetration. Findings showed that the definitions generated by men with a history of perpetration were less likely to include nonpenetrative sexual violence and were more likely to use gender/sex-specific language. We conclude that most young men have a generally accurate understanding of rape, though perpetrators' understandings may be somewhat narrower and more limited than those without a history of perpetration. We end with recommendations for refocusing sexual education curricula to better aid in the prevention of sexual violence perpetration. Specifically, given that (most) men know what rape is, educators should emphasize the cultural and situational factors that make rape more likely so all people can reduce the risk of sexual violence and take proactive precautions to prevent it.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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