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Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions

2016· review· en· W2431527081 on OpenAlexafffund
Sharmistha Mishra, Marie‐Claude Boily, Sheree Schwartz, Chris Beyrer, James Blanchard, Stephen Moses, Delivette Castor, Nancy Phaswana‐Mafuya, Peter Vickerman, Fatou Drame, Michel Alary, Stefan Baral

Bibliographic record

VenueAnnals of Epidemiology · 2016
Typereview
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalUniversity of ManitobaUniversity of TorontoSt. Michael's Hospital
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institute of Nursing ResearchFogarty International CenterNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingCenter for AIDS Research, Johns Hopkins UniversityImperial College LondonCanadian Institutes of Health ResearchCenter for AIDS Research, University of WashingtonNational Institutes of HealthNational Institute on Drug AbuseNational Institute of Diabetes and Digestive and Kidney DiseasesJohns Hopkins University
KeywordsSex workMedicineHuman immunodeficiency virus (HIV)Work (physics)Men who have sex with menData scienceFamily medicineComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.058
metaresearch head score (Gemma)0.166
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.058
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.166
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0090.009
Science and technology studies0.0010.003
Scholarly communication0.0030.007
Open science0.0050.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.533
GPT teacher head0.545
Teacher spread0.012 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations44
Published2016
Admission routes2
Has abstractno

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