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Record W2803333311 · doi:10.1177/0886260518777012

Unraveling the Personality Profile of the Sexual Murderer

2018· article· en· W2803333311 on OpenAlexaff
Éric Beauregard, Matt DeLisi

Bibliographic record

VenueJournal of Interpersonal Violence · 2018
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPersonality disordersPersonalityPsychologyPoison controlAntisocial personality disorderInjury preventionSuicide preventionSex offenseHuman factors and ergonomicsClinical psychologyPsychiatryOccupational safety and healthSexual abuseMedicineMedical emergencySocial psychology

Abstract

fetched live from OpenAlex

Although sexual homicide offenders (SHOs) evince personality disorders, few prior studies have examined all personality disorders or utilized control groups of offenders. Drawing on data from 616 adult male sex offenders including 85 who were SHOs, the current study examined the personality profile of the SHOs, by comparing them with a group of violent nonhomicidal sex offenders (VNHSOs) and a group of nonhomicidal sex offenders (NHSOs) on clinical diagnostics of personality disorders and various crime characteristics. The personality profile of SHOs is comprised primarily of Schizoid and Borderline Personality Disorders, and these offenders were significantly likely to select a victim, use a weapon, and use drugs and alcohol before their offenses, but less likely to force their victim to engage in sexual acts or humiliate them. The comorbidity of Schizoid, Borderline, and Antisocial Personality Disorder features presents unique personality dysfunction that facilitates the lethal sexual violence of SHOs relative to their nonhomicidal sexual offender peers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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.

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

Citations37
Published2018
Admission routes1
Has abstractyes

Explore more

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