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Record W1983316343 · doi:10.1111/1556-4029.12462

The Relationship Between Mental Disorders and Types of Crime in Inmates in a Brazilian Prison

2014· article· en· W1983316343 on OpenAlexaff
Milena Pereira Pondé, Jean Caron, Milena Siqueira Santos Mendonça, Antônio Carlos Cruz Freire, Nicolas Moreau

Bibliographic record

VenueJournal of Forensic Sciences · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of OttawaMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsPsychiatryPsychologyPersonality disordersPrisonPsychosisExtortionHomicideClinical psychologySchizophrenia (object-oriented programming)Antisocial personality disorderSuicide preventionPersonalityPoison controlInjury preventionMedicineCriminologyMedical emergency

Abstract

fetched live from OpenAlex

This cross-sectional study conducted in prisons in the city of Salvador, Bahia, Brazil, investigated the association between the presence of psychiatric disorders in 462 prisoners and the types of crimes committed by them. Psychiatric diagnosis was obtained by means of the Brazilian Portuguese version of the Mini-International Neuropsychiatric Interview. A statistically significant association was found between some psychiatric disorders and specific groups of crime: lifelong substance addiction with sex crimes and homicide; antisocial personality disorder with robbery and with kidnapping and extortion; borderline personality disorder with sex crimes; and lifelong alcohol addiction with fraud and conspiracy and with armed robbery and murder. It was concluded that the mental disorders considered more severe (psychosis and bipolar disorder) were not associated with violent crimes, suggesting that the severity of the psychotic disorder may be the factor that has caused psychosis to be associated with violent crimes in previous 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.353
Teacher spread0.313 · 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 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

Citations19
Published2014
Admission routes1
Has abstractyes

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