Healthcare use for diarrhoea and dysentery in actual and hypothetical cases, Nha Trang, Viet Nam.
Bibliographic record
Abstract
To better understand healthcare use for diarrhoea and dysentery in Nha Trang, Viet Nam, qualitative interviews with community residents and dysentery case studies were conducted. Findings were supplemented by a quantitative survey which asked respondents which healthcare provider their household members would use for diarrhoea or dysentery. A clear pattern of healthcare-seeking behaviours among 433 respondents emerged. More than half of the respondents self-treated initially. Medication for initial treatment was purchased from a pharmacy or with medication stored at home. Traditional home treatments were also widely used. If no improvement occurred or the symptoms were perceived to be severe, individuals would visit a healthcare facility. Private medical practitioners are playing a steadily increasing role in the Vietnamese healthcare system. Less than a quarter of diarrhoea patients initially used government healthcare providers at commune health centres, polyclinics, and hospitals, which are the only sources of data for routine public-health statistics. Given these healthcare-use patterns, reported rates could significantly underestimate the real disease burden of dysentery and diarrhoea.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".