Evaluative Attitudes May Explain the Link Between Injunctive Norms and Sexual Aggression
Bibliographic record
Abstract
The current study examined the extent to which evaluative attitudes toward sexual aggression (i.e., positive or negative evaluative judgments about sexually aggressive behavior) mediate the association between injunctive norms (i.e., extent to which peers approve or disapprove of sexually aggressive behavior) and self-reported sexual aggression against women. Participants were 200 male undergraduate students. Approximately one in four males reported engaging in at least one sexually aggressive act since the age of 16. Participants with a history of sexual aggression also reported the highest likelihood of engaging in sexually aggressive behavior in the future. We tested two separate mediation models to examine the extent to which evaluative attitudes account for the link between injunctive norms and sexual aggression: one model with self-reported history of sexual aggression as the outcome and the other with likelihood of engaging in sexually aggressive behavior as the outcome. Results showed that more positive evaluative attitudes toward sexual aggression accounted for the association between injunctive norms and self-reported history of sexual aggression. Similarly, evaluative attitudes accounted for the link between injunctive norms and self-reported likelihood of engaging in sexually aggressive behavior in the future. Overall, these findings are consistent with theoretical and empirical explanations of sexual offending and general criminal behavior; however, this is the first study to explore the relationship between injunctive norms and evaluative attitudes in the context of explaining sexually aggressive behavior. If more rigorous research establishes a causal relationship between injunctive norms, evaluative attitudes, and sexually aggressive behavior, this would suggest that targeting these factors in prevention programs may reduce sexual aggression by male undergraduate students.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".