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Record W2097427854 · doi:10.1177/1079063215569542

Acquaintance Rape

2015· article· en· W2097427854 on OpenAlexaff
Robert Lehmann, Alasdair M. Goodwill, R. Karl Hanson, Klaus-Peter Dahle

Bibliographic record

VenueSexual Abuse · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsPublic Safety CanadaToronto Metropolitan University
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

The aim of the current study was to enhance the assessment and predictive accuracy of risk assessments for sexual offenders by utilizing detailed crime scene analysis (CSA). CSA was conducted on a sample of 247 male acquaintance rapists from Berlin (Germany) using a nonmetric, multidimensional scaling (MDS) Behavioral Thematic Analysis (BTA) approach. The age of the offenders at the time of the index offense ranged from 14 to 64 years (M = 32.3; SD = 11.4). The BTA procedure revealed three behavioral themes of hostility, criminality, and pseudo-intimacy, consistent with previous CSA research on stranger rape. The construct validity of the three themes was demonstrated through correlational analyses with known sexual offending measures and criminal histories. The themes of hostility and pseudo-intimacy were significant predictors of sexual recidivism. In addition, the pseudo-intimacy theme led to a significant increase in the incremental validity of the Static-99 actuarial risk assessment instrument for the prediction of sexual recidivism. The results indicate the potential utility and validity of crime scene behaviors in the applied risk assessment 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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.007

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 head0.078
GPT teacher head0.343
Teacher spread0.265 · 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 designNot applicable
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

Citations15
Published2015
Admission routes1
Has abstractyes

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