Perceptions of Sexual Assault: Effects of Victim Physiological Arousal and Victim Gender on Jurors’ Decisions
Bibliographic record
Abstract
Limited research has assessed juror decision making in cases of female perpetrated sexual assault and the role played by factors such as the victim’s gender, physiological arousal, and participant’s gender in the decision making process. Participants (n = 215) were presented with one of four trial vignettes that varied the perpetrator and victim’s gender and victim’s physiological arousal. The impact of these variables was examined on guilty verdicts rendered, credibility, and blameworthiness of the victim and accused. Results demonstrate that the male victim was blamed more than the female victim. Further, male participants viewed the male victim to be less credible than the female victim. Lastly, male participants viewed the accused to be more credible when the victim was depicted as a male with signs of physiological arousal. The results reveal the disadvantages a male victim of female perpetrated sexual assault may face if he pursues his sexual assault at trial. Keywords: sexual assault, rape myths, juror bias, gender, physiological arousal
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".