Working with economically vulnerable women engaged in sex work: Collaborating with community stakeholders in Southern Uganda
Bibliographic record
Abstract
Economically vulnerable women engaged in sex work (WESW) comprise one of the key populations with higher prevalence of HIV globally. In Uganda, HIV prevalence among WESW is estimated at 37% and accounts for 18% of all new infections in the country. This paper describes the strategies by which we have engaged community stakeholders in a randomised clinical trial aimed at evaluating the efficacy of adding economic empowerment components to traditional HIV risk reduction to reduce the incidence of STIs and HIV among WESW in Uganda. We demonstrate that stakeholder engagement, including the engagement of WESW themselves, plays a critical role in the adaptation, implementation, uptake, and potential sustainability of evidence-based interventions. To our knowledge, this is the first study to utilise stakeholder engagement involving WESW in Uganda. Researchers working with hard-to-reach populations, such as WESW, are encouraged to invest time and resources to engage key stakeholders through a full range of collaborative activities; and ensure that research is culturally appropriate and meets the needs of all stakeholders involved.Clinical trial registration ClinicalTrials.gov identifier: NCT03583541.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".