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Record W2048937282 · doi:10.1080/09540120500159482

Cruising for sex: Sexual risk behaviours and HIV testing of men who cruise, inside and outwith public sex environments (PSE)

2005· article· en· W2048937282 on OpenAlexaboutno aff
Jamie Frankis, Paul Flowers

Bibliographic record

VenueAIDS Care · 2005
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsDemographyMen who have sex with menPopulationCondomPublic healthMedicineHuman immunodeficiency virus (HIV)Quarter (Canadian coin)Sexual intercourseReproductive healthPsychologyEnvironmental healthGeographySyphilisFamily medicine

Abstract

fetched live from OpenAlex

This paper describes sexual risk behaviours and HIV testing amongst men who cruise an urban public sex environment (PSE) in southern England. Data were collated using a cross-sectional survey (response rate = 56%; n=216), sampling men from directly within the PSE. As such, this represents the first peer-review study generalizable to the wider population of urban PSE users. The current sample reflect a highly sexually active population, almost one-third (31%) reported over 50 sex partners in the last year. However, just one-quarter (26%) reported unprotected anal intercourse (UAI) with at least one partner outside of a 'safer sexual strategy'. Almost 1 in 12 (7%) reported UAI within the PSE. Over two-thirds (71%) had had a named HIV test of whom 16% had tested HIV positive. Just one-third (34%) of negative/untested PSE users had tested within the previous two years. Positive men were significantly more likely to report unsafe sex within the PSE in the last year. PSE users report lower levels of UAI than men in the local gay community but higher HIV prevalence. PSE-based UAI remains an HIV (re)infection risk. In concert, these findings suggest the importance of in situ targeted health promotion to prevent PSE-based risks.

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 score0.116
Threshold uncertainty score0.741

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.100
GPT teacher head0.386
Teacher spread0.286 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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