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Record W2507427650 · doi:10.1037/cbs0000016

Educating Canadian jurors about the not criminally responsible on account of mental disorder defence.

2015· article· en· W2507427650 on OpenAlexvenueaboutno aff
Evelyn M. Maeder, Susan Yamamoto, Kristin L. Fenwick

Bibliographic record

VenueCanadian Journal of Behavioural Science/Revue canadienne des sciences du comportement · 2015
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsnot available
FundersAmerican Psychology-Law Society
KeywordsPsychologySocial psychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.327
GPT teacher head0.314
Teacher spread0.013 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2015
Admission routes2
Has abstractyes

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