Educating Canadian jurors about the not criminally responsible on account of mental disorder defence.
Bibliographic record
Abstract
Previous research has demonstrated the prevalence of negative attitudes toward the insanity defence in the United States, but attitudes toward the not criminally responsible on account of mental disorder (NCRMD) defence in Canada have yet to be examined. Two studies investigated whether educating mock jurors about the NCRMD defence would change their attitudes toward the defence and verdict decisions. We also investigated potential differences between student and community samples in such cases. In Study 1, we found that educating jurors about the NCRMD defence led to more positive attitudes toward the defence, but it did not affect verdicts. In Study 2, we found no effect of NCRMD education on attitudes or verdict decisions. Results did reveal an effect of sample type on the 'injustice and danger' dimension of NCRMD attitudes, such that students had more positive attitudes toward the defence than did community members. Verdicts did not vary as a function of sample type, suggesting that students may be an acceptable proxy for mock jurors in these types of studies.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".