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Record W2340829483 · doi:10.1177/1079063216630983

The Relationships Between Victim Age, Gender, and Relationship Polymorphism and Sexual Recidivism

2016· article· en· W2340829483 on OpenAlexaff
Skye Stephens, Michael C. Seto, Alasdair M. Goodwill, James M. Cantor

Bibliographic record

VenueSexual Abuse · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCentre for Addiction and Mental HealthRoyal Ottawa Mental Health CentreToronto Metropolitan University
Fundersnot available
KeywordsRecidivismPsychologyDemographyInjury preventionClinical psychologyPoison controlMedicineMedical emergencySociology

Abstract

fetched live from OpenAlex

Victim choice polymorphism refers to victim inconsistency in a series of offenses by the same perpetrator, such as in the domains of victim age, victim gender, and victim-offender relationship. Past studies have found that victim age polymorphic offenders have higher rates of sexual recidivism than offenders against adults only and offenders against children only. Few studies, however, have examined gender and relationship polymorphism, or accounted for the impact of the number of past victims. The present study analyzed the relationship between polymorphism and sexual recidivism, while controlling for the number of victims. The sample consisted of 751 male adult sexual offenders followed for an average of 10 years, 311 of whom were polymorphic (41% of the total sample). The main finding suggested that there was an association between sexual recidivism and age and relationship polymorphism; however, these associations were no longer significant after controlling for the number of victims.

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)0.008
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.103
GPT teacher head0.317
Teacher spread0.214 · 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

Citations23
Published2016
Admission routes1
Has abstractyes

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