A test of gender–crime congruency on mock juror decision-making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study was to investigate whether jurors would be biased in favor of guilt when a defendant’s gender was congruent with stereotypes associated with certain crimes (i.e. a gender–crime congruency effect) and the role of juror gender in informing such an effect. A gender balanced sample (N = 200) of participants read a six-page fabricated grand theft of a motor vehicle or shoplifting trial transcript, in which we manipulated defendant gender. Results did not support the prediction that a woman charged with shoplifting and a man charged with auto theft would yield harsher decisions among same-gender mock jurors. However, there was a significant juror gender by crime-type interaction effect on defendant impressions. For jurors who were women, shoplifting was associated with more positive defendant impressions, with no such effect for men. While this study did not provide evidence of a gender–crime congruency effect, future researchers should consider other crime types and moderator variables.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it