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Record W4303423654 · doi:10.1177/08862605221127199

Developmental Sequela for Sexual Homicide: Testing an Integrated Multi-Theoretical Model

2022· article· en· W4303423654 on OpenAlexaffabout
Julien Chopin, Matt DeLisi, Éric Beauregard

Bibliographic record

VenueJournal of Interpersonal Violence · 2022
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité LavalUniversité de MontréalSimon Fraser University
Fundersnot available
KeywordsPsychologyPoison controlPersonalityHomicideInjury preventionHuman factors and ergonomicsSuicide preventionDevelopmental psychologyClinical psychologyOccupational safety and healthPersonality disordersCommissionMedicineSocial psychologyMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

Research focusing on the role of adverse childhood experience (ACE) of individuals involved in sexual homicide (SH) is scarce. Theoretical models of SH have postulated a connection between these adverse experiences and the development of internal risk factors. However, such assumptions have never been empirically tested. Therefore, the current research aims to identify how ACEs affect the development of personality disorders and problematic behaviors during adolescence, which constitute internal risk factors for the commission of SH. The sample comes from a database including 613 individuals involved in sexual crimes in Canada among which 60 committed a SH. Bivariate and multiple regression analyses were conducted to identify personality disorders and problematic behaviors during adolescence associated with the presence of ACEs. Next, path analysis was used to identify the direct and indirect relationships between ACEs, internal risk factors, and the commission of SH. Results showed that individuals who experienced ACEs were more likely to develop internal risk factors involved in the commission of SH. Moreover, findings suggest that the impact of these adverse experiences will differ, depending on whether the child has been victim of violence or if he/she has witnessed it.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.072
GPT teacher head0.340
Teacher spread0.267 · 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 designSimulation or modeling
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

Citations6
Published2022
Admission routes2
Has abstractyes

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