Environmental inequality and disparities in school readiness: The role of neurotoxic lead
Bibliographic record
Abstract
Abstract Developmental science has increasingly scrutinized how environmental hazards influence child outcomes, but few studies examine how contaminants affect disparities in early skill formation. Linking research on environmental inequality and early childhood development, this study assessed whether differences in exposure to neurotoxic lead explain sociodemographic gaps in school readiness. Using panel data tracking a representative sample of 1266 Chicago children (50% female, 16% White, 30% Black, 49% Hispanic, μ age = 5.2 months at baseline, collected 1994–2002), analyses quantified the contribution of lead contamination to class and racial disparities in vocabulary skills and attention problems at ages 4 and 5. Results suggested that lead contamination explains 15%–25% and 33%–66% of the disparities in each outcome, respectively, although imprecise estimates preclude drawing firm inferences about attention problems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".