The influence of race on jurors’ perceptions of lethal police use of force.
Bibliographic record
Abstract
OBJECTIVE: Many highly publicized police use-of-force encounters have recently occurred in the United States. This project primarily explored whether officer, juror, or victim race affects verdicts in trials involving police use of force. HYPOTHESES: Because of recent conflicting research surrounding race and juror decision-making, we conducted an exploratory analysis on the interactive effects of juror, victim, and defendant race. We hypothesized that mock jurors with favorable perceptions of police legitimacy would be less likely to convict an officer charged with manslaughter. METHOD: Four hundred sixteen (243 women, 170 men, three another gender; 263 White, 50 Asian, 44 Black, 41 Latine, four Native American, 14 another race/ethnicity) jury-eligible community members read a trial transcript involving a police officer charged with manslaughter, in which we manipulated victim and defendant race (Black, White), then rendered a verdict and answered a questionnaire. RESULTS: We found significant effects of police legitimacy and defendant race on verdicts. The main effect was qualified by an interaction between juror race/ethnicity and defendant race. Simple-slope analyses revealed no effect of defendant race for White mock jurors. In comparison, Black, indigenous, and people of color (BIPOC) mock jurors were significantly more likely to convict a White than a Black defendant. We also observed significant effects of police legitimacy, defendant race, and victim race on perceptions of the officer's use of force. CONCLUSIONS: Our analyses revealed that mock jurors were significantly more punitive when the defendant was White compared with Black, and they perceived the officer's use of force as significantly more excessive when the officer was White or the victim was Black. These effects appear to be driven primarily by BIPOC jurors. Mock jurors with more favorable perceptions of police legitimacy were significantly less likely to convict the officer and viewed his use of force as less excessive. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".