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Record W2073910816 · doi:10.1108/20093829201100004

Abuse Histories and Attributions of Sexual Offenders

2011· article· en· W2073910816 on OpenAlexaff
Sandy Jung, Elizabeth A. Carlson

Bibliographic record

VenueJournal of Criminal Psychology · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsMacEwan University
Fundersnot available
KeywordsPsychologyDenialSexual abuseAttributionLocus of controlClinical psychologyPhysical abuseEmpathyChild abuseDevelopmental psychologyCognitionPoison controlSuicide preventionPsychiatrySocial psychologyMedicineMedical emergencyPsychotherapist

Abstract

fetched live from OpenAlex

The current study is an exploratory study examining the relationship between the abuse histories of 89 sexual offenders and the constructs of locus of control, sexual attitudes, general empathy, and denial. Of the 89 offenders, 14.6% were sexually abused, 13.5% physically abused, and 9% both sexually and physically abused, with 61.5% having no abuse history. Analyses indicated that motivation to change was higher for abused versus non‐abused offenders, and that those who were sexually abused had significantly more cognitive distortions about children than those who experienced physical abuse. Although no differences emerged in locus of control scores, our findings indicated that physically abused offenders were more able to take on the perspective of others than those who have not experienced physical abuse. The findings provide several avenues to pursue in examining the longstanding effects of abuse in the thinking and cognitions of sexual offenders.

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)0.001
metaresearch head score (Gemma)0.018
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.140
GPT teacher head0.363
Teacher spread0.223 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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