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Record W2556679483 · doi:10.1111/1556-4029.13223

Incapacity of the Mind Secondary to Medication Misuse as a Not Criminally Responsible Defense

2016· article· en· W2556679483 on OpenAlexaffabout
Sébastien Prat, Bruno J. Losier, Heather M. Moulden, Gary Chaimowitz

Bibliographic record

VenueJournal of Forensic Sciences · 2016
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsAutomatism (medicine)PsychiatryPsychologyJurisdictionDiminished responsibilityInsanity defenseForensic psychiatryMedicineCriminologyLawPolitical scienceInsanity

Abstract

fetched live from OpenAlex

The manifestations of disorders of the mind may play a role in the occurrence of criminal behavior. In the majority of the cases, the presence of a psychiatric disorder is cited as the reason that an individual was not fully aware of his behavior. However, other conditions, such as seizure disorders or hypoglycemia, have also been linked to an inability to understand the nature and consequences of one's actions. On occasion, these situations can be explained by a state of automatism that may be described as insane or noninsane. In this article, we describe the case of a 77-year-old man, suffering from Parkinson's disease, where the issue of criminal responsibility associated with incapacity of the mind secondary to medication misuse was raised. We elaborate on the thinking behind this opinion and the implications according to Canadian law. Although the legal outcome of this case is specific to our jurisdiction, the clinical implication may be common to any patient suffering from a similar condition and may inform physicians, families, and lawyers.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.406
Teacher spread0.323 · 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 designOther design
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

Citations3
Published2016
Admission routes2
Has abstractyes

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