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Record W4283702449 · doi:10.1002/bsl.2577

The defense of mental disorder and crimes against the person committed under the influence of cannabis: A Canadian perspective

2022· article· en· W4283702449 on OpenAlexaffabout
Simon‐Pierre Bernard‐Arevalo, Laura Dellazizzo, Émilie Marceau, Alexandre Dumais

Bibliographic record

VenueBehavioral Sciences & the Law · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité de MontréalInstitut national de psychiatrie légale Philippe-PinelUniversité Laval
Fundersnot available
KeywordsInsanity defenseOperationalizationCannabisPerspective (graphical)PsychologyPsychiatryPsychopathologyForensic psychiatryLegalizationVerdictCriminologyInsanityPolitical scienceLaw

Abstract

fetched live from OpenAlex

The legalization of cannabis raises many queries, one of which regards the criminal liability of users under the influence of cannabis when crimes against the person are committed. This perspective review consequently aims to examine the defense of mental disorder (also referred to as the insanity defense) in Canadian criminal law and revise court decisions involving cases with cannabis use rendered in the field between 1995 and 2021. The purpose was to specify the factors allowing Canadian criminal courts to grant or refuse the defense of mental disorder to help further operationalize the jurisprudential criteria for forensic practice. We noted that presence of a severe and persistent primary psychopathology was the most decisive factor when determining the verdict of the accused who consumed cannabis.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.640

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.009
Science and technology studies0.0050.009
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.325
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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