“But He’s a Star Football Player!”: How Social Status Influences Mock Jurors’ Perceptions in a Sexual Assault Case
Bibliographic record
Abstract
There have been several recent, high-profile cases in the media that have shed light on the perceived leniency in sentencing defendants in sexual assault cases. In a number of these cases, the defendant was well known within their community (e.g., Brock Turner; People v. Turner ) or nationally (e.g., Ghomeshi; R v. Ghomeshi ). The purpose of this study was to examine how the social status of the defendant (low vs. high), victim social status (low vs. high), victim gender (male vs. female), and the reason the victim was unconscious during the assault (consuming alcohol vs. consuming cold medicine) influenced mock jurors’ decisions in a sexual assault case. Mock jurors ( N = 489) read a mock trial transcript depicting an alleged sexual assault. Mock jurors were asked to render a dichotomous verdict, continuous guilt rating, and rate their perceptions of the victim and defendant. There was no influence of the variables on mock jurors’ dichotomous verdicts; however, social status influenced guilt ratings. There also was a combined influence of the defendant’s social status and the reason the victim was unconscious such that when the defendant was described as low status, and the victim was unconscious due to alcohol consumption, the defendant received higher guilt ratings compared with when the victim was unconscious due to cold medicine. Moreover, the victim was perceived as having more control over the situation when the defendant was the star quarterback (i.e., high status), the victim was female, and she was unconscious due to alcohol consumption compared with cold medicine. These results suggest that victims may be blamed based on their perceived social status and other factors that may have influenced their control over the sexual assault, such as alcohol consumption.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".