Beyond the Evidence: How Race, Chronological Age, and Developmental Age Shape Juror Verdicts in Sexual Assault Cases
Bibliographic record
Abstract
There is an overrepresentation of Indigenous people (both as accused and victims of crime) and those with developmental delays in the Canadian Criminal Justice System. The current research examined the influence of defendant and victim race (involving Indigenous people), as well as defendant developmental and chronological age, on mock-jurors' perceptions and decisions in sexual assault cases. Experiment 1 examined the influence of defendant and victim race (Indigenous or White), and defendant chronological age (16- or 36-year). Experiment 2 examined defendant race (Indigenous or White), defendant developmental age (14- or 24-year), and defendant chronological age (14- or 24-year). In both experiments, mock-jurors rendered more guilty verdicts when the defendant was White, compared to Indigenous. Mock-jurors also were more lenient to the chronologically younger defendant in Experiment 1 and the developmentally younger defendant in Experiment 2. Finally, mock-jurors' acceptance of rape myths was assessed; higher endorsement was associated with lower guilt ratings.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".