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Record W4401343693 · doi:10.1080/26929953.2024.2386518

What is the “Sex” in Sex Addiction? Problem Behaviors Reported Among Those Endorsing Compulsive Sexual Behavior

2024· article· en· W4401343693 on OpenAlexaff
Joshua B. Grubbs, Brinna N. Lee, Christopher G. Floyd, Beáta Bőthe, Todd L. Jennings, Shane W. Kraus

Bibliographic record

VenueSexual Health & Compulsivity · 2024
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversité de Montréal
FundersInternational Center for Responsible Gaming
KeywordsSexual behaviorPsychologySexual addictionAddictionHypersexualityClinical psychologyCompulsive behaviorDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Recent years have seen a surge in research related to compulsive, excessive, or out-of-control sexual behaviors. Yet, little is known about which behaviors people might experience as compulsive. Using YouGov America, a non-probability sample was collected, matched to U.S. representative norms, stratified, and weighted based on sample characteristics to ensure representativeness (N = 2,806; Mean Age = 48.9, SD = 17.3). Participants reported if they had experienced any concerns about their sexual behaviors being either “out of control” or “an addiction.” Participants who endorsed such concerns were then asked to indicate which behaviors had led to such concerns, using a checklist of 11 potentially overlapping sexual behaviors (e.g. frequent casual sexual encounters, using apps to find sexual partners). Men—both heterosexual and gay/bi/other–were more likely to report concerns that their sexual behaviors were an addiction, relative to heterosexual women. Relative to heterosexual women, men of any sexual orientation were more likely to report pornography use as a specific behavior of concern, and less likely to report partnered sexual behaviors. More religious participants were more likely to endorse masturbation as a behavior of concern and less likely to endorse frequent casual sexual encounters.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.398
Teacher spread0.339 · 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 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

Citations15
Published2024
Admission routes1
Has abstractyes

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