Gestational Age and Child Development at Age Five in a Population‐Based Cohort of Australian Aboriginal and Non‐Aboriginal Children
Bibliographic record
Abstract
BACKGROUND: Preterm birth and developmental vulnerability are more common in Australian Aboriginal compared with non-Aboriginal children. We quantified how gestational age relates to developmental vulnerability in both populations. METHODS: Perinatal datasets were linked to the Australian Early Development Census (AEDC), which collects data on five domains, including physical, social, emotional, language/cognitive, and general knowledge/communication development. We quantified the risk of developmental vulnerability on ≥1 domains at age 5, according to gestational age and Aboriginality, for 97 989 children born in New South Wales, Australia, who started school in 2009 or 2012. RESULTS: Seven thousand and seventy-nine children (7%) were Aboriginal. Compared with non-Aboriginal children, Aboriginal children were more likely to be preterm (5% vs. 9%), and developmentally vulnerable on ≥1 domains (20% vs. 36%). Overall, the proportion of developmentally vulnerable children decreased with increasing gestational age, from 44% at ≤27 weeks to 20% at 40 weeks. Aboriginal children had higher risks than non-Aboriginal children across the gestational age range, peaking among early term children (risk difference [RD] 19.0, 95% confidence interval [CI] 16.3, 21.7; relative risk [RR] 1.91, 95% CI 1.77, 2.06). The relation of gestational age to developmental outcomes was the same in Aboriginal and non-Aboriginal children, and adjustment for socio-economic disadvantage attenuated the risk differences and risk ratios across the gestational age range. CONCLUSIONS: Although the relation of gestational age to developmental vulnerability was similar in Aboriginal and non-Aboriginal children, Aboriginal children had a higher risk of developmental vulnerability at all gestational ages, which was largely accounted for by socio-economic disadvantage.
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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 | 0.001 |
| 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) | 0.001 | 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".