Examining Implicit and Explicit Evaluations of Sexual Aggression and Sexually Aggressive Behavior in Men Recruited Online
Bibliographic record
Abstract
The purpose of the current study was to explore the relationship between implicit and explicit evaluations of sexual aggression and indicators of sexually aggressive behavior in samples of students and community men recruited online. Participants were male undergraduate students recruited online from a Canadian University ( N = 150) and men recruited from the community via an online panel ( N = 378). Participants completed measures of implicit and explicit evaluations of sexual aggression, cognitive distortions regarding rape, self-reported past sexually aggressive behavior, and self-reported proclivity to commit sexually aggressive behavior. We found that more positive explicit evaluations and more cognitive distortions were moderately to strongly associated with sexual aggression; however, this was not the case for implicit evaluations of rape. Our results suggest that explicit evaluations of sexual aggression and cognitive distortions may be relevant for understanding sexual aggression against adults, and that more research is needed exploring whether or not implicit evaluations are associated with sexually aggressive behavior.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".