Profile of Female Sex Workers in a Chinese County: Does It Differ by Where They Came from and Where They Work?
Bibliographic record
Abstract
Since the 1980s, informal or clandestine sex work in the service or entertainment industry has spread from municipalities to small towns in most areas of China. Despite recognition of the important role of female sex workers in HIV and STD epidemics in China, limited data are available regarding their individual characteristics and the social and environmental context of their work. Furthermore, most existing studies on commercial sex in China have been conducted in large cities or tourist attractions. Using data from 454 female sex workers in a rural Chinese county, the current study was designed to explore the individual profiles of commercial sex workers and to examine whether the profile and sexual risk behaviour differ by where the female sex workers came from and where they work. The sample in the current study was different from previous studies in a number of key individual characteristics. However, similarly to previous studies, the subjects in the current study were driven into commercial sex by poverty or limited employment opportunities, lived a stressful life, were subject to sexual harassment and related violence, and engaged in a number of health-compromising behaviours including behaviours that put them at risk of HIV/STD infection and depression. The findings of the current study underscore the urgent need for effective HIV/STD prevention, intervention and mental health promotion programs among female sex workers in China. The data in the current study suggest a strong association of individual profile with the economic conditions of work sites and residence status (in-province residency vs. out-of-province residency), which suggests that such efforts must take the social and cultural contextual factors of working environment (and sexual risks) into consideration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".