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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 OpenAlexaff
Kévin Nolet, Alexa L. Wilson, Joanne L. Rouleau

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.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.213
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

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 designTheoretical or conceptual
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

Citations6
Published2017
Admission routes1
Has abstractyes

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