Examining the Prejudicial Effects of Gang Evidence on Jurors
Bibliographic record
Abstract
This study was designed to examine the potential biasing effects of gang association on mock juror verdicts. Three hundred and fifteen undergraduate psychology students watched one of three versions of a simulated trial that included opening and closing arguments by the defense and prosecution, together with direct and cross-examination of the investigating officer and the victim/eyewitness. The three versions differed only in regard to mention of the defendant's gang association. Gang association was manipulated by having the defendant described as either seen hanging out with gang members on the night of the incident (gang affiliate) or being a documented gang member with a gang tattoo (hardcore gang member). In the control condition, no mention of gangs was made. As predicted, when testimony on gang affiliation was introduced, guilty verdicts increased significantly. Overall, participants were more likely to find the defendant guilty in the gang affiliate and hardcore gang conditions when compared to the no-gang control condition. Various explanations for this effect are examined, and the implications of these data are discussed.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| 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".