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Record W3035642455 · doi:10.1002/9781119439325.ch7

Indirect and Physiological Approaches to Assessing Deviant Sexual Interests

2020· other· en· W3035642455 on OpenAlexaff
Kevin L. Nunes, Chloe I. Pedneault

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCarleton University
Fundersnot available
KeywordsSexual arousalPsychologyConstruct (python library)Construct validityDevelopmental psychologySexual abuseChild sexual abuseArousalClinical psychologySexual behaviorSocial psychologyPoison controlInjury preventionPsychometricsMedicineMedical emergency

Abstract

fetched live from OpenAlex

This chapter reviews the evidence regarding the construct validity of penile plethysmography (PPG) and of indirect measures designed to assess sexual interest in children. For PPG, it focuses on comparisons of men who have committed sexual offenses against children with those who have not, and comparisons of sexual offenders against children (SOCs) who went on to sexually recidivate with those who did not. The chapter briefly reviews the more limited evidence regarding the construct validity of PPG and indirect measures designed to assess sexual interest in sexual assault (e.g., rape) against adults. It considers the even more limited evidence regarding the incremental validity of PPG and indirect measures of deviant sexual interest. Sexual attraction is usually inferred from the amount of penile arousal in response to deviant stimuli (e.g., stories about sexual abuse of a child, rape) relative to nondeviant stimuli (e.g., stories about consenting sex between adults).

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.288
GPT teacher head0.349
Teacher spread0.061 · 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 designBench or experimental
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

Citations3
Published2020
Admission routes1
Has abstractyes

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