A Rapid Ethnography to Inform a Biobehavioural HIV Preventions Study Among Venezuelan Migrant Sex Workers in Peru: A Protocol of Formative Multidisciplinary Methods
Bibliographic record
Abstract
The Venezuelan refugee crisis has triggered Latin America’s largest mass migration, displacing over a fifth of the country’s population. A significant number of migrants have sought refuge in neighboring countries like Peru. Within this context, Venezuelan migrants confront an array of vulnerabilities, including xenophobia and economic hardship, which have compelled some to sex work for their livelihoods. Venezuelan sex workers (VSWs) in Peru face amplified challenges, including heightened risks for HIV and sexually transmitted and blood-borne infections (STBBIs) and exposure to various forms of violence. Addressing the urgent need to comprehend and enhance HIV and STBBI preventive services tailored to this marginalized group in Peru’s capital is paramount. Our biobehavioural HIV prevention study combines sequential mixed methods: we start with a rapid ethnography, followed by semi-structured interviews and finally incorporate cross-sectional surveys with HIV and STBBI testing. The present study protocol presents the integrated and initial rapid ethnographic component of the study which explores the dynamics of street-based sex work in Lima and the sociocultural narratives surrounding VSWs. Data collection will involve systematic fieldnote taking including non-person photos during in-person and virtual participant observation. This comprehensive approach will provide a nuanced understanding of the complex landscape of sex work and HIV/STBBI vulnerabilities among VSWs in Lima. The rapid ethnography endeavors to offer valuable insights that can underpin evidence-based healthcare interventions, specifically tailored to cater to the unique requirements of this marginalized population.
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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 | 0.019 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".