The Impact of Nutrition during Early Childhood on Education among Guatemalan Adults
Bibliographic record
Abstract
Early childhood nutrition is thought to have important effects on education, broadly defined to include various forms of learning. We advance beyond previous literature on the effect of early childhood nutrition on education in developing countries by using unique longitudinal data begun during a nutritional experiment during early childhood with educational outcomes measured in adulthood. Estimating an intent-to-treat model capturing the effect of exposure to the intervention from birth to 36 months, our results indicate significantly positive, and fairly substantial, effects of the randomized nutrition intervention a quarter century after it ended: increased grade attainment by women (1.2 grades) via increased likelihood of completing primary school and some secondary school; speedier grade progression by women; a one-quarter SD increase in a test of reading comprehension with positive effects found for both women and men; and a one-quarter SD increase on nonverbal cognitive tests scores. There is little evidence of heterogeneous impacts with the exception being that exposure to the intervention had a larger effect on grade attainment and reading comprehension scores for females in wealthier households. The findings are robust to an array of alternative estimators of the standard errors and controls for sample attrition
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".