Predictors of mobility among women engaged in commercial sex work in Uganda using generalized estimating equations model
Bibliographic record
Abstract
BACKGROUND: Women engaged in commercial sex work (WESW) are at a higher risk of acquiring and transmitting HIV. WESW are highly mobile, and their mobility may increase their economic status, and increased access to healthcare and other social services. However, it may also facilitate the spread of HIV infection from higher to lower prevalence regions. This study examined the predictors of mobility among WESW in Uganda using a generalized estimating equations model. METHODS: We defined and measured mobility as the change in residence by WESW between baseline, 6 months, and 12 months follow-up. Participants who changed places were considered mobile, and those who never changed were non-mobile. We used data from a longitudinal study, which recruited 542 WESW from Southern Uganda aged 18-55 years and constructed a Generalized Estimating Equations Model. RESULTS: Findings show that 19.6% of WESW changed residence between baseline and 6 months of follow-up and 26.2% (cumulative) between baseline and 12 months of follow-up. Older women (OR = 0.966, 95% CI = 0.935, 0.997) were associated with decreased odds of mobility, whereas WESW who were HIV positive (OR = 1.475, 95% CI = 1.078, 2.018) and those from large households (OR = 1.066, 95% CI = 1.001, 1.134) were associated with increased odds of mobility. WESW residing in rural areas (OR = 0.535, 95% CI = 0.351, 0.817) were associated with decreased odds of mobility compared to those from fishing sites. CONCLUSION: The results indicate risk factors for mobility, further research is needed to determine the directionality of these factors in order to design interventions addressing mobility among WESW.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".