Bringing Community Back to Community Health Worker Studies: Community interactions, data collection, and health information flows
Bibliographic record
Abstract
Community Health Workers (CHWs) have the potential to be a great resource in the further growth of the fledging healthcare systems that exist in many developing countries. Through their position as community members, CHWs can interact with other individuals in the areas where they live and work and serve as valuable health resources by providing basic health information and referrals up the healthcare chain. However, few studies have examined CHWs from a community-based perspective. This study analyzes the work and relationships of several CHWs working for the Mashavu mHealth venture in Nyeri, Kenya. Through the use of participant observation and interviews, the workflows of these CHWs were investigated with a specific eye towards interactions between CHWs and their communities and how these interactions affect potential health data collection opportunities. This community-based perspective reveals unique insights into the workflows of the CHWs and how technology might be designed to support them.
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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 | 0.029 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| 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".