How can sanitary infrastructures reduce child malnutrition and health inequalities? Evidence from Guatemala
Why this work is in the frame
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Bibliographic record
Abstract
With the propensity score matching method, we carried out an average benefit incidence analysis that helps disclose those who really benefited from the sanitary services in Guatemala. Specifically, we tested the role of income, maternal education and social capital on how sanitary infrastructures affect child health. Results indicated that the child health benefits from infrastructure increase (decrease) with the household's socio-economic status when the infrastructure is a complement (substitute) of the private inputs provided by the household, and that the role of the infrastructure (complement or substitute) itself depends on the household's socio-economic status. Finally, results revealed that the battle against child malnutrition and health inequalities could be improved by combining sanitary infrastructure investments with effective public promotion of maternal education, social trust, and poverty reduction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it