Are there nutrient-based poverty traps?
Bibliographic record
Abstract
A key question in development economics is whether nutritional deficiencies generate intergenerational poverty traps by reducing the earnings potential of children born into poverty.To assess the causal influence on human capital of one of the most widespread micronutrient deficiencies, supplemental iron pills were made available at a local health center in rural Peru and adolescents were encouraged to take them up via classroom media messages.Results from school administrative records provide novel evidence that reducing iron deficiency results almost immediately in a large and significant improvement in school performance.For anemic students, an average of 10 100mg iron pills over three months improves average test scores by 0.4 standard deviations and increases the likelihood of grade progression by 11%.Supplementation also raises anemic students' aspirations for the future.Both results indicate that cognitive deficits from iron-deficiency anemia contribute to a nutrition-based poverty trap.Our findings also demonstrate that, with low-cost outreach efforts in schools, supplementation programs offered through a public clinic can be both affordable and effective in reducing rates of adolescent IDA.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".