Gender Differences in Cognitive and Affective Responses to Sexual Coercion
Bibliographic record
Abstract
This study examined gender differences in responses to sexual coercive experiences in mixed-sex (male-female) relationships. Participants were 112 women and 28 men who had experienced sexual coercion and completed measures of cognitive (attributions to self, attributions to the coercer, internal attributions) and affective (guilt, shame) self-blame, trauma symptoms, and upset at the time of the incident) with respect to their most serious or upsetting sexually coercive experience. The women were more upset than were the men at the time of the incident. Contrary to predictions, the men and women did not differ in the extent to which they attributed blame to themselves or the strength of their internal attributions, guilt, or shame. Both the men and women attributed more blame to the coercer than to themselves; however, the women attributed more blame to the coercer than did the men. The women reported more trauma symptoms than the men did which was related to the finding that more women than men had experienced sexual coercion involving physical force. These results are discussed in terms of the similarities and differences between men's and women's cognitive and affective responses to sexual coercion.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".