Gender Differences in Sexual Coercion Perpetration: Investigating the Role of Alcohol-use and Cognitive Risk Factors
Bibliographic record
Abstract
Studies have shown that alcohol is involved in 50 to 75% of all sexual coercion situations. Significant associations have been established between alcohol-use and sexual coercion perpetration and cognitive factors have been proposed to play an important role in this association. However, the current knowledge on the relationship between alcohol-use, cognitive factors, and sexual coercion perpetration is mostly based on male samples. Therefore, the purpose of this article is to investigate gender differences associated with the role of alcohol-use and cognitive factors in sexual coercion perpetration. To do so, 742 participants (562 women, 180 men) completed an online questionnaire assessing (1) alcohol-use, (2) perpetration of sexual coercion, and (3) cognitions related to sexuality or alcohol (misperception of sexual intent, alcohol-related expectancies, alcohol-related rape myth acceptance [RMA]). Results revealed that (1) for both men and women, alcohol-use as well as cognitive variables allowed to discriminate perpetrators from non-perpetrators, (2) perpetrators, whether male or female, did not differ significantly on any of the risk factors, except for alcohol-related RMA, (3) a prediction model that considered cognitive variables, as well as alcohol-use significantly contributed to the explanation of both male and female sexual coercion, and (4) the prediction model explained three times the amount of variance in sexual coercion perpetrated by men compared to women. On the one hand, these results highlight similarities in risk factors towards sexual coercion perpetration for both men and women. Perpetrators, regardless of their gender, seem to exhibit similar alcohol-use, alcohol-related expectancies, and tendencies to misinterpret sexual intent, making these risk factors potential prevention and intervention targets for both genders. On the other hand, these results emphasize the need to break away from male-based sexual coercion explanatory models and consider other variables towards a better understanding of female sexual coercion perpetration.
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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 | 0.000 | 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".