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Record W247531994 · doi:10.1177/070674371506000307

The National Trajectory Project of Individuals Found Not Criminally Responsible on Account of Mental Disorder in Canada. Part 4: Criminal Recidivism

2015· article· en· W247531994 on OpenAlexafffundvenueabout
Yanick Charette, Anne G. Crocker, Michael C. Seto, Leila Salem, Tonia L. Nicholls, M. Caulet

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsBC Mental Health & Substance Use ServicesUniversity of British ColumbiaRoyal Ottawa Mental Health CentreMcGill UniversityDouglas Mental Health University InstituteUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsRecidivismSeriousnessPsychologySample (material)Criminal justicePsychiatryDemographyCriminologyPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine criminal recidivism rates of a large sample of people found not criminally responsible on account of mental disorder (NCRMD) in Canada's 3 most populous provinces, British Columbia, Ontario, and Quebec. Public concern about the dangerousness of people found NCRMD has been fed by media attention on high-profile cases. However, little research is available on the rate of reoffending among people found NCRMD across Canadian provinces. METHOD: Using data from the National Trajectory Project, this study examined 1800 men and women in British Columbia (n = 222), Ontario (n = 484), and Quebec (n = 1094) who were found NCRMD between May 2000 and April 2005 and followed until December 2008. RESULTS: Recidivism was relatively low after 3 years (17%). There were interprovincial differences after controlling for number of prior criminal offences, diagnosis, seriousness of the index offence, and supervision by the review boards. British Columbia (10%) and Ontario (9%) were similar, whereas Quebec had almost twice the recidivism (22%). People who had committed severe violent index offences were less likely to reoffend than those who had committed less severe offences. People from the sample were less likely to reoffend when under the purview of review boards, across all 3 provinces. CONCLUSION: The results of this study, along with other research on processing differences, suggest systemic differences in the trajectories and outcomes of persons found NCRMD need to be better understood to guide national policies and practices.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.330
Teacher spread0.246 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations73
Published2015
Admission routes4
Has abstractyes

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