Reaching marginalized young women for HIV prevention in Botswana: a pilot social network analysis
Bibliographic record
Abstract
Almost one-fifth of Botswana's population is infected with HIV. The Inter-Ministerial National Structural Intervention Trial is a trial to test the impact on HIV rates of a structural intervention that refocuses government structural support programs in favor of young women. Ensuring that the intervention reaches all vulnerable young women in any given community is a challenge. Door-to-door recruitment was inefficient in previous work, so we explored innovative ways to reach this population. We sought to understand the support networks of marginalized young women, and to test the possibility of using social networks to support universal recruitment in this population. Ego-centric and sociometric analyses were used to describe the support networks of marginalized young women. Marginalized young women go to other women and relatives for support, and they communicate face to face rather than using social media. Network maps show how young women were connected to each other. Lessons from the pilot include a better understanding of how to use social networks as a recruitment method, such as the time required and the types of community members that can help. Social networks could help reach other hard-to-reach populations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".