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Record W4408245472 · doi:10.1002/jia2.26425

Community leadership is key to effective HIV service engagement for female sex workers in Africa

2025· article· en· W4408245472 on OpenAlexaff
Primrose Matambanadzo, Lilian Otiso, Sibonile Kavhaza, Parinita Bhattacharjee, Frances M. Cowan

Bibliographic record

VenueJournal of the International AIDS Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineSex workersHuman immunodeficiency virus (HIV)Men who have sex with menSex workCommunity engagementKey (lock)Service (business)Public relationsFamily medicineEnvironmental healthPopulationPolitical scienceResearch methodology

Abstract

fetched live from OpenAlex

Although overall HIV incidence has declined across sub-Saharan Africa since 2010, HIV incidence among female sex workers is nine times higher than among cisgender women [1]. Young women who sell sex are particularly vulnerable. Women who sell sex do so in the context of discrimination and intense stigma, exacerbated by the criminalization of sex work [2]. Despite impressive population-level gains in treatment cascade engagement, antiretroviral therapy (ART) coverage and rates of viral suppression have remained lower among African female sex workers than in the general population [3]. Addressing female sex workers’ specific HIV prevention and treatment needs remains central to a comprehensive HIV response and remains one of UNAIDS central pillars for “ending AIDS by 2030.”

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 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)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0110.004
Scholarly communication0.0080.005
Open science0.0030.018
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0280.004

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 head0.079
GPT teacher head0.352
Teacher spread0.273 · 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 designQualitative
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

Citations6
Published2025
Admission routes1
Has abstractyes

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