Racial Bias in Mock Juror Decision-Making: A Meta-Analytic Review of Defendant Treatment.
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
Common wisdom seems to suggest that racial bias, defined as disparate treatment of minority defendants, exists in jury decision-making, with Black defendants being treated more harshly by jurors than White defendants. The empirical research, however, is inconsistent--some studies show racial bias while others do not. Two previous meta-analyses have found conflicting results regarding the existence of racial bias in juror decision-making (Mazzella & Feingold, 1994, Journal of Applied Social Psychology, 24, 1315-1344; Sweeney & Haney, 1992, Behavioral Sciences and the Law, 10, 179-195). This research takes a meta-analytic approach to further investigate the inconsistencies within the empirical literature on racial bias in juror decision-making by defining racial bias as disparate treatment of racial out-groups (rather than focusing upon the minority group alone). Our results suggest that a small, yet significant, effect of racial bias in decision-making is present across studies, but that the effect becomes more pronounced when certain moderators are considered. The state of the research will be discussed in light of these findings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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