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Record W3122994364

The Impact of Nutrition during Early Childhood on Education among Guatemalan Adults

2006· preprint· en· W3122994364 on OpenAlexaboutno aff
John A. Maluccio, John Hoddinott, Jere R. Behrman, Reynaldo Martorell, Agnes Quisumbing, Aryeh D. Stein

Bibliographic record

VenueScholarly Commons (University of Pennsylvania) · 2006
Typepreprint
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)AttritionEducational attainmentEarly childhoodIntervention (counseling)Reading comprehensionDevelopmental psychologyPsychologyTest (biology)Early childhood educationDemographyMedicineGerontologyReading (process)Geography
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.235
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2006
Admission routes1
Has abstractyes

Explore more

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