S14.1 Transitions around sex work and their significance in STI/HIV epidemics
Bibliographic record
Abstract
In many regions of the world, the importance of formal sex work in driving HIV epidemics is well-established and it is recognised that female sex workers (FSWs) experience a disproportionately high risk of HIV globally. Sex work and sex work networks are complex and continuously evolving and therefore FSW research needs to address this changing nature of HIV risk as well as the contribution of other important factors to the overall HIV epidemic, such as macro-structural determinants, sub-population-level social and sexual networks, individual behaviours and host and viral biological factors. Further, early HIV and STI risk has been particularly identified as being an important area of programmatic and research focus. In an effort to understand the complexity and risk trajectory associated with sex work, the “Transitions” study examines the HIV risk and vulnerability among young women and FSWs over the life course from the structural, network, behavioural and biological perspectives. Transitions also aims to dissect the contribution and interaction of factors within these different areas (structural, network, behavioural and biological) that drive HIV risk and transmission at an individual- and population-level. Disentangling the role of these contributing factors in HIV risk could shed light on the optimal mix of HIV interventions that is proportionate to the relative influence of these drivers. This presentation will introduce a framework that demonstrates how Transitions brings together the various perspectives in its work in the different epidemiological contexts of Ukraine and Kenya. For the latter, mapping results from Ukraine and Kenya will be reviewed. This presentation will also show how such a framework is used to guide research and inquiry in order to generate meaningful and concrete findings that could have implications on HIV prevention and control programming.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.085 | 0.008 |
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".