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Record W3010822174 · doi:10.3138/cjhs.2019-0055

Establishing Canadian metrics for self-report measures used to assess hypersexuality

2020· article· en· W3010822174 on OpenAlexaffvenueabout
Drew A. Kingston, Mark E. Olver, Enya Levaque, Megan L. Sawatsky, Michael C. Seto, Martin L. Lalumière

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2020
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of OttawaUniversity of SaskatchewanRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsHypersexualityPsychologySexual behaviorHuman sexualitySexual addictionCompulsive behaviorClinical psychologySexual dysfunctionSexual desireDemographyPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

We examined the prevalence of hypersexuality in two combined Canadian adult community samples totalling 1,857 respondents (female n = 960, male n = 835, other n = 60, missing n = 2). Participants were recruited from social media to complete an online sexual behaviour survey that included two measures of compulsive sexual behaviour disorder— the Sexual Compulsivity Scale (SCS) and Hypersexual Behaviour Inventory (HBI)—as well as sexual behaviour and interest items. Respondents also reported their total sexual outlets (TSO)—defined by number of orgasms experienced weekly—as a third potential indicator of hypersexuality. Canadian men and women reported multiple sexual outlets per week that tended to be higher than previous reports. Men tended to report a larger number and higher frequency of various sexual behaviour than women, including higher rates of compulsive sexual behaviour disorder, which varied depending on the measure employed. Implications for establishing sexuality norms and conceptualizing hypersexuality and compulsive sexual behaviour disorder are discussed.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.275
GPT teacher head0.402
Teacher spread0.127 · 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 designNot applicable
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

Citations17
Published2020
Admission routes3
Has abstractyes

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