Are They Guilty Because of Their Gender?
Bibliographic record
Abstract
This paper explores whether sexual acts of varying degrees of misconduct/violence are judged differently depending on the gender of the actor and the subject. It presents pooled data from four countries regarding the actors and subjects involved in a range of sexual activities. In addition, the paper investigates whether the gender of the observer (study participant) influenced the assessment. Our sample consisted of 3416 students from the United States, Israel, Finland, and Estonia. The research instrument contained 8 sexual scenarios where the gender labels of the actors and subjects were manipulated. In several highly revealing cases, it was found that female actors were assessed more benignly compared to male ones. Men were never assessed more benignly. Our research finding is in line with public records showing that women are less frequently perceived and reported as sexual perpetrators. As a consequence, men may find it more difficult to complain of sexual misconduct against them, and sexual misconduct by women against men may have remained uncounted and disregarded in many cases.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".