Talking about a Black Man: The Influence of Defendant and Character Witness Race on Jurors' Use of Character Evidence
Why this work is in the frame
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Bibliographic record
Abstract
To determine whether anti-Black bias influences mock jurors' use of character evidence (i.e., information about a defendant's personality), this study manipulated the race (Black, White) of the defendant and character witness and the type of character evidence presented in a fictitious criminal trial. Two hundred six predominantly White participants read a trial transcript, then made verdicts and trial judgments. Results confirm previous findings that positive character evidence has a limited impact on jurors' judgments, but negative character evidence is misused to evaluate the defendant's guilt. However, participants were more influenced by character evidence that was inconsistent with racial stereotypes. Specifically, positive character evidence had a stronger effect for Black defendants, whereas negative rebuttal evidence had a stronger influence for White defendants. The race of the character witness did not affect judgments. Thus, defendant race may provide a framework that influences how mock jurors process character evidence.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it