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Record W4283328850 · doi:10.1080/00224499.2022.2086962

A Test of Three Different Explanations for Low Stimulus Response Discrimination in Phallometric Testing

2022· article· en· W4283328850 on OpenAlexaff
Skye Stephens, Michael C. Seto, Martin L. Lalumière

Bibliographic record

VenueThe Journal of Sex Research · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsPsychologyStimulus (psychology)Developmental psychologyCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

Phallometric assessment is used to assess men’s sexual interest in children and to assist in risk assessment and treatment planning. A common response pattern, especially when the assessment is conducted in a forensic context, is an indiscriminate pattern of penile responses: No sexual stimulus seems to produce a substantially higher response than another. This indiscriminate response profile could be the result of (1) faking good (in particular, reducing the responses to child stimuli); (2) floor or ceiling effects caused by low or high arousability, or (3) non-exclusivity (the individual is similarly sexually interested in both children and adults). In this study of 2,858 adult male patients who underwent volumetric phallometric assessment for sexual interest in children between 1995 and 2011, we tested these three possible explanations. Results showed support for each of the explanations, but the variance accounted for in response discrimination was quite small when considering each explanation (separately or when considered together). We discuss avenues for future research to better discern the causes of indiscriminate responding in phallometric assessment.

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)0.013
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.222
GPT teacher head0.442
Teacher spread0.220 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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