Gender Differences in Sexual Violence Victimization Experiences and Validity of Victimization Reports: A Think-Aloud Study
Bibliographic record
Abstract
This study compared the qualitative nature of women and men's sexual violence (SV) victimization, the types of experiences captured and missed on the Sexual Experiences Survey-Short Form Victimization (SES-SFV) across genders, and common interpretations of the SES-SFV items. Fifty-four university students (31 women, 21 cis men, 2 trans men) who had recent unwanted (but not necessarily nonconsensual) sexual experiences thought out loud while privately completing the SES-SFV. They also typed descriptions of experiences reported on SES-SFV items or similar experiences when nothing was reported on an item. Results indicated that women's victimization was more frequent and severe than cis men's, except when men were victimized by men. Although verbal coercion was common across genders, event descriptions indicated that women's verbal coercion experiences were more often harsh and part of a partner's ongoing SV or coercive control. The findings suggest that quantitative measurement can mask important gender differences in victimization and (based on analysis of false positives and negatives) may underestimate rape and attempted rape experiences, especially women's. Findings suggested that responding to the SES-SFV was not traumatic or distressing. However, participants sometimes expressed confusion about the items and interpreted them in unintended ways.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".