Esengo ya Bosembo (“Joy of Equity”): Development of an Advocacy Video to Reduce Stigma and to Promote Sexual and Reproductive Health and Rights of Women Sex Professionals in Pointe-Noire, Congo Republic
Bibliographic record
Abstract
Sex workers experience elevated risks of sexual and gender-based violence (SGBV) from intimate partners, clients, and community members that harms health and human rights. While SGBV contributes to poorer sexual and reproductive health (SRH) outcomes among sex workers, including elevated human immunodeficiency virus (HIV) vulnerabilities, stigma targeting sex workers reduces SRH service access and uptake. The Congo Republic is an exemplar context to address stigma toward sex workers. Sex workers' HIV prevalence (8.1%) in Congo Republic is double the national prevalence, yet research indicates that nearly one-fifth (17.2%) of sex workers in Congo Republic avoid health care because of stigma and discrimination. This Resources, Frameworks, & Perspectives article describes the process of developing Esengo ya Bosembo ("Joy of Equity"), a culturally tailored advocacy video that aims to reduce health care and community stigma toward women sex professionals (e.g., sex workers) in Pointe-Noire, Congo Republic. This knowledge translation product stems from a participatory mapping intervention with sex professionals in Pointe-Noire that revealed the need for sensitization tools and activities to reduce sex work stigma among health care providers and community members. The video incorporates three overarching key messages: (1) sex professionals are human beings with equal rights to dignity, protection, and health services; (2) elevated risks of SGBV and stigma targeting sex workers reduce SRH service access and uptake; and (3) participatory mapping is a potential way to empower sex professionals to share their experiences and recommendations for change. This article details how health promotion practitioners and sex professionals may use the video to advocate for change.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".