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Record W2758054311 · doi:10.1016/j.sexol.2017.09.001

Using the dual control model to understand problematic sexual behaviors in men

2017· article· en· W2758054311 on OpenAlex
Kévin Nolet, Alexa L. Wilson, Joanne L. Rouleau

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSexologies · 2017
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDual (grammatical number)PsychologyControl (management)Developmental psychologyComputer scienceArtificial intelligenceArt

Abstract

fetched live from OpenAlex

A strong sexual response in men is associated to a variety of sexual behaviors that can result in severe consequences, like hypersexuality, sexual risk-taking, and sexual coercion. However, considering a sexual response as an “out of control” impulse fails to take into account regulation and inhibition factors involved in these types of behaviors. The Dual Control model proposes that the strength of the sexual response depends on the balance between excitation and inhibitory systems. The goal of the present review is to demonstrate the usefulness of this model in understanding problematic sexual behaviors in both heterosexual and homosexual men. Empirical studies identify three main processes associated to the three control systems of this model: a sexual response that is too strong, a lack of inhibition of this response, and inhibition provoked by the preoccupation of sexual performance. Clinicians as well as researchers should thus consider excitation and inhibition factors when treating and conducting research on problematic sexual behaviors.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.616

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.213
GPT teacher head0.423
Teacher spread0.210 · 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