Canadian Mock Juror Attitudes and Decisions in Domestic Violence Cases Involving Asian and White Interracial and Intraracial Couples
Bibliographic record
Abstract
This study manipulated the race of the defendant and the victim (White/White, White/Asian, Asian/Asian, and Asian/White) in a domestic violence case to examine the potential prejudicial impact of race on juror decision making. A total of 181 undergraduate students read a trial transcript involving an allegation of spousal abuse in which defendant and victim race were manipulated using photographs. They then provided a verdict and confidence rating, a sentence, and responsibility attributions, and completed various scales measuring attitudes toward wife abuse and women. Findings revealed that female jurors were harsher toward the defendant than were male jurors. When controlling for attitudes toward Asians, jurors found the defendant guilty more often in cases involving interracial couples, as compared to same-race couples. Path analyses revealed various factors and attitudes involved in domestic violence trial outcomes. Findings contribute to the scarce literature on legal proceedings involving Asians, particularly in domestic violence cases. Outcomes also provide a model for relevant factors and characteristics of jurors in domestic violence cases. Roadblocks inherent in jury research are also 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".