Risk Markers for Poor Developmental Attainment in Young Children
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To evaluate social and environmental determinants of poor developmental attainment among preschool children by means of longitudinal data from a population-based sample of Canadian children. DESIGN: Secondary analysis of data from cycles 1 (1994-1995) and 2 (1996-1997) of the National Longitudinal Survey of Children and Youth using a cohort design with 2-year follow-up. PARTICIPANTS: A total of 4987 children aged 1 to 5 years at baseline, whose biological mother completed risk factor information and who were included in both cycles. MAIN OUTCOME MEASURES: Poor developmental attainment (developing unusually slowly) was defined as scores more than 1 SD below the age-standardized mean for the Motor and Social Development Scale, revised Peabody Picture Vocabulary Test, or Canadian Achievement Tests in mathematics and reading/comprehension, depending on the child's age. RESULTS: The prevalence of sustained poor developmental attainment after 2 years of follow-up was 4.6%. Factors found to be associated with poor developmental attainment included male sex (odds ratio [OR], 1.37; 95% confidence interval [CI], 1.10-1.70), maternal depression (OR, 1.64; 95% CI, 1.25-2.15), low maternal education (OR, 1.57; 95% CI, 1.19-2.08), maternal immigrant status (OR, 1.93; 95% CI, 1.38-2.71), and household low income adequacy (OR, 1.43; 95% CI, 1.11-1.83). CONCLUSIONS: Having a mother who has symptoms of depression, has low education, or is an immigrant, and living in a household with low income adequacy increase the risk of poor developmental attainment in children aged 1 to 5 years. The notable risks associated with these factors indicate them as possible targets for screening and interventions to prevent poor developmental attainment.
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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 it