From individuals to complex systems: exploring the sexual networks of men who have sex with men in three cities of Karnataka, India
Bibliographic record
Abstract
INTRODUCTION: Research on the HIV vulnerability of men who have sex with men (MSM) in India has tended to focus on aggregates of individual risk behaviours. However, such an approach often overlooks the complexities in the sexual networks that ultimately underpin patterns of spread. This paper analyses a set of sexual contact network (SCN) snapshots in relation to ethnographic findings to reorientate individual-level explanations of risk behaviour in terms of more complex systems. METHODS: Fifteen community researchers conducted a 2-month ethnographic study in three cities in Karnataka to generate descriptions of the risk environments inhabited by MSM. SCNs were reconstructed by two methods. First, initial participants, defined as nodes of various sexual networks, were purposively sampled. In each site, six nodes brought in three sexual partners separately as participants. In all sites, 72 participants completed 431 surveys for their 7-day sexual partners. Second, each site determined four groups representing various sexual networks, each group containing four individuals. In all sites, 48 participants completed 334 surveys for their regular sexual partner. RESULTS: Considerable differences were observed between sites for practically all included behavioural variables. On their own, these characteristics yielded contradictory interpretations with respect to understanding contrasts in HIV prevalence at each site. However, viewing these variables in relation to SCNs and ethnographic data produced non-linear interpretations of HIV vulnerability which suggested importance to local interventions. CONCLUSION: SCN data may be used with existing data on risk behaviour and the structural determinants of vulnerability to re-tailor more tightly focused interventions.
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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) | 0.001 | 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".