Bibliographic record
Abstract
BACKGROUND: Myanmar (Burma), with an upper estimate of 400,000 people living with HIV/AIDS, faces a dangerous and potentially devastating epidemic. Female sex workers in the country are one of the most affected populations, with high prevalence rates of both HIV and sexually transmitted infections (STIs). METHODS: A qualitative study was undertaken in Yangon at the end of 2002 to investigate the social and demographic features contributing to the transmission of HIV among female sex workers in urban Myanmar. Twenty-seven key informants from the government, non-government organisations (NGOs), international non-government organisations (INGOs), private sector and the United Nations system agencies and 25 women currently working in the sex trade were interviewed. RESULTS: The sex trade in Yangon is rapidly growing and is characterised by a high degree of complexity. The number of female sex workers is estimated to be between 5,000 and 10,000 and there are approximately 100 brothels operating in various townships around the city. Nearly one-third of the women in the study reported previous imprisonment for offences related to sex work as well as fear of harassment, sexual exploitation, violence and gang rape. Almost half reported using condoms with clients at all times. Contradicting views exist as to the level of awareness about STIs and HIV among Yangon sex workers, with the majority never having been tested for HIV. Only one-quarter of women were regular patients of the limited number of STI clinics operated by INGOs. CONCLUSIONS: Female sex workers in Myanmar remain a highly marginalised group almost inaccessible due to a variety of legal, political, cultural and social factors and are particularly vulnerable to HIV and STIs. It is important to encourage partnerships between INGOs by promoting service coordination and information sharing to increase the availability of services for sex workers and to build political support for an unpopular cause.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".