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Record W2008434475 · doi:10.1136/sextrans-2011-050404

Sexual behaviour and risk reduction strategies among a multinational sample of women who have sex with women

2012· article· en· W2008434475 on OpenAlexaboutno aff
Vanessa Schick, Joshua G. Rosenberger, Debby Herbenick, Michael Reece

Bibliographic record

VenueSexually Transmitted Infections · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsnot available
FundersIndiana University Bloomington
KeywordsMedicineReproductive healthSex organDemographyClinical psychologyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: The development of safer sex recommendations for women who have sex with women (WSW) remains challenging given a limited understanding of sexual behaviour between women. The present study was conducted in order to investigate the sexual repertoires of WSW and the safer sex methods they use to reduce the likelihood of sexually transmitted infection acquisition. METHODS: An online survey targeted towards women with desire, attraction or previous sexual behaviour with women was distributed globally. Women (N=3116) who engaged in at least one sexual act with a woman in the previous year and were currently living in the USA, UK, Canada or Australia were included in the present study. Questions were based upon previously validated items in nationally representative studies. RESULTS: Participants indicated a wide diversity of sexual behaviours with the majority of women reporting a history of genital rubbing (99.8%), vaginal fingering (99.2%), genital scissoring (90.8%), cunnilingus (98.8%) and vibrator use (74.1%). Barrier use was reported by a minority (<25%) of the participants. CONCLUSIONS: The variety of sexual acts reported by the sample points to the need for the development of more contextually appropriate sexual health guidelines for WSW.

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)0.001
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 score0.027
Threshold uncertainty score0.989

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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

Citations50
Published2012
Admission routes1
Has abstractyes

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