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Clients of Indoor Commercial Sex Workers: Heterogeneity in Patronage Patterns and Implications for HIV and STI Propagation Through Sexual Networks

2007· article· en· W1981219056 on OpenAlex
Valencia P. Remple, David M. Patrick, Caitlin Johnston, Mark Tyndall, Ann Jolly

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSexually Transmitted Diseases · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of British ColumbiaBC Centre for Disease Control
Fundersnot available
KeywordsMedicineSex workersProxy (statistics)Sex workCategorizationDemographyFemale sexHuman immunodeficiency virus (HIV)Environmental healthFamily medicinePopulationStatisticsResearch methodology

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine whether "high-risk" clients occupied important sociometric positions in sexual networks of commercial sex workers and to estimate whether they were more likely to be HIV and STI infected. GOAL: To determine whether a classification of high-risk clients could be validated by network analysis. STUDY DESIGN: We used proxy data on clients collected from a cross-sectional survey of 49 indoor female sex workers. RESULTS: Two types of clients were categorized as high risk, including those who created sexual bridges between sex establishments and those who had sex with most or all the FSW at an establishment. High-risk clients were significantly more central and were more likely to be members of cohesive subgroups than were lower-risk clients. The few known HIV and STI infections were in high-risk clients. CONCLUSIONS: It is possible to identify theoretically high-risk commercial sex clients from the network perspective using simple data collection and categorization approaches.

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.

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)0.000
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 score0.044
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.023
GPT teacher head0.322
Teacher spread0.299 · 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