Aboriginal Canadians in the Courtroom: Effects of Defendant and Eyewitness Race on Juror Decision-Making in a Criminal Trial
Bibliographic record
Abstract
Negative stereotypes, some concerning alcohol use, about Aboriginal Canadians permeate Canadian society.This study explored whether racial bias affects jurors' perceptions of Aboriginal Canadian eyewitnesses, particularly when the eyewitness was intoxicated during the crime, as well as the effect of defendant race.Participants read a trial transcript in which eyewitness intoxication and both eyewitness/defendant race (Aboriginal Canadian/White) were manipulated, provided a verdict, and responded to a series of questions about the eyewitness.Although sober witnesses were perceived more favourably than intoxicated witnesses, intoxication had no effect on verdicts.Participants rated Aboriginal eyewitnesses as more accurate than White eyewitnesses, with no differences in credibility or deception.Finally, there was no effect of defendant race on verdicts.Although this study failed to demonstrate a convincing effect of racial bias, further work must be conducted in order to ensure that all citizens are subject to a fair trial by an impartial jury.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".