The Effect of Brazil's Family Health Program on Cognitive Skills
Bibliographic record
Abstract
ABSTRACT This paper examines the effect of Brazil's Family Health Program (Programa Saude da Familia, FHP) on cognitive skills (measured by test scores) of fifth‐grade students. We use biennial data from national exams between 2007 and 2015, and variation in the FHP implementation date across municipalities, birth cohort, and test year to identify the effect of the program on language and mathematics test scores. In municipalities in the North and Northeast regions, students exposed to FHP at or before birth score 0.72 points higher in language and 0.98 points higher in mathematics than those first exposed later, corresponding to 0.0194 sd and 0.0259 sd in intent‐to‐treat estimates. We further show that early exposure to FHP is associated with improvements in test scores in municipalities with lower income and limited access to basic public health infrastructure, such as access to running water and sewage, providing further evidence that the program benefitted economically disadvantaged municipalities the most. Heterogeneity analyses reveal no significant differences by student gender or mother's education, but important differences by race, as the program effects are concentrated among mixed‐race and Black students. Our findings are consistent with health‐related channels playing an important role, rather than measured parental engagement, although the precise mechanisms cannot be directly identified with the available data.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".