The socio-economic gradient of child development: cross-sectional evidence from children 6-42 months in Bogota
Bibliographic record
Abstract
We study the socio-economic gradient of child development on a representative sample of low- and middle-income children aged 6-42 months in Bogota, using the Bayley Scales of Infant Development, a high quality test based on direct observation of the child's abilities. We find a statistically significant difference between children in the 90th and 10th percentile of the wealth distribution in our sample of 0.33 standard deviations (SD) in cognition, 0.29 SD in receptive language and 0.38 SD in expressive language at 14 months. The socio-economic gap increases substantially with age to 1 SD (cognition), 0.80 SD (receptive language) and 0.69 SD (expressive language) by 42 months. While the gap persists after controlling for mediating factors such as parental and biomedical characteristics, the level of stimulation in the home, and the quality of the institutional care setting; its size is significantly reduced by variables related to the home environment - i.e. parental investments in care quantity and quality. These findings have important implications for the design of well-targeted, effective and timely interventions that promote early childhood development.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".