Sexual behaviour and risk reduction strategies among a multinational sample of women who have sex with women
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".