Perceptions of Sexual Harassment Perpetrators: The Mediating Role of Identification and Emotions
Bibliographic record
Abstract
Within sexual harassment and rape literature victims are often blamed to some degree for their misfortune. Victim characteristics have been extensively researched; however there is a dearth in research on perceptions of perpetrators. This study examines the issue from a social identity perspective, and proposes that men will identify more with a perpetrator than women, will feel more empathy and less anger and disgust towards a perpetrator, will evaluate his characteristics more positively, will engage in reinterpretation of the perpetrators behaviour in order to excuse his behaviour, and will blame the perpetrator less and the victim more than women. Additionally this effect was expected to be attenuated for men when the perpetrator was Canadian (outgroup member) and enhanced when he was Australian (ingroup member). Australian university students (N = 167) read a scenario where a male student (Canadian or Australian) harasses a female student, and then responded to a questionnaire assessing their perceptions of the perpetrator and the events as well as their emotional reactions. Gender differences were found for perpetrator blame and victim derogation, and the relationship between gender and these variables was mediated by identification, anger and disgust. No effect of perpetrator nationality was found.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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".