MétaCan
Menu
Back to cohort
Record W2167004340 · doi:10.1177/107906320001200403

Alcohol and Drug Abuse in Sexual and Nonsexual Violent Offenders

2000· article· en· W2167004340 on OpenAlexaff
Jeffrey Abracen, Jan Looman, Dana Anderson

Bibliographic record

VenueSexual Abuse · 2000
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsPsychologyAggressionSexual abuseSubstance abuseAddictionClinical psychologyPoison controlInjury preventionPsychiatryMedical emergencyMedicine

Abstract

fetched live from OpenAlex

According to a literature review by Marshall (1996), presently available data have not clarified the proportion of sexual offenders who would meet diagnostic criteria for addictive problems. Our own literature review failed to find published studies comparing sexual offenders to nonsexual violent offenders on standardized measures of substance abuse. Our study is a preliminary investigation of the differences between sexual offenders (rapists: n = 72; child molesters: n = 34) and nonsexual violent offenders (n = 24) on measures of alcohol and drug abuse. The findings indicate that sexual offenders were more likely to abuse alcohol than were nonsexual violent offenders. Nonsexual offenders were significantly more likely to have had a history of other forms of substance abuse. The results are considered in terms of theories of alcohol's contribution to aggressive behavior and sexual aggression. Implications for assessment and treatment of sexual offenders 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)0.001
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.296
Teacher spread0.272 · 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

Citations79
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueSexual AbuseSame topicPsychopathy, Forensic Psychiatry, Sexual OffendingFrench-language works237,207