China’s Sex Worker Health Policies: The Influence of Transnational Actors and Their Limitations
Bibliographic record
Abstract
This chapter is about the influence of transnational actors on China’s sex worker health policies. While the policing of prostitution in China is a story of domestic law and politics, the public health approach to regulating sex work in China starts in the international global health community. It then makes its way into central government health institutions in Beijing, and trickles down into the lives of local state health workers and the sex workers in their community. These transnational roots matter: they have shaped both the content of sex work health policies and the public health officials who manage their administration. Indeed, the approach that China’s health policies and officials endorse for gauging the prevalence of HIV/AIDS and reducing its occurrence among sex workers, and the language these authorities use, reflect best practices in the global public health community. Yet the obstacles that Chinese health agents encounter result in practices that fall short of these ideals and harm sex workers. That often grim reality is the subject of the next chapter. What I highlight in this chapter is how the global public health community working in China to support the creation of HIV/AIDS policies seems disengaged from what actually happens on the ground.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".