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Record W2116743307 · doi:10.1177/0093854807299462

Instrumentally Violent Youths

2007· article· en· W2116743307 on OpenAlexaff
Jillian Flight, Adelle E. Forth

Bibliographic record

VenueCriminal Justice and Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton UniversityHealth Canada
Fundersnot available
KeywordsPsychopathyPsychologyEmpathyPoison controlPsychological interventionInjury preventionHuman factors and ergonomicsDark triadClinical psychologySuicide preventionConstruct (python library)Developmental psychologyPersonalityPsychiatrySocial psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

Psychopathy in adults has been well documented as a robust predictor of violence. Explanations for this relation have focused on the affective deficit that characterizes psychopathy. This study examined the relations among psychopathic traits, empathy, attachment, and motivations for violence in 51 incarcerated adolescent offenders. Psychopathy scores were related to both instrumental and reactive violence. Youths who were classified as instrumentally violent scored higher on psychopathy than those who were not, which could be attributed to the interpersonal and affective features of psychopathy. These findings provide support for the construct of psychopathy existing in youths. Implications of the current study for potential interventions and prevention of persistent violent offending are discussed.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.358
Teacher spread0.310 · 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

Citations148
Published2007
Admission routes1
Has abstractyes

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