Preschool attendance and developmental outcomes at age five in Indigenous and non-Indigenous children: a population-based cohort study of 100 357 Australian children
Bibliographic record
Abstract
BACKGROUND: Policies to increase Australian Indigenous children's participation in preschool aim to reduce developmental inequities between Indigenous and non-Indigenous children. This study aims to understand the benefits of preschool participation by quantifying the association between preschool participation in the year before school and developmental outcomes at age five in Indigenous and non-Indigenous children. METHODS: We used data from perinatal, hospital, birth registration and school enrolment records, and the Australian Early Development Census (AEDC), for 7384 Indigenous and 95 104 non-Indigenous children who started school in New South Wales, Australia in 2009/2012. Preschool in the year before school was recorded in the AEDC. The outcome was developmental vulnerability on ≥1 of five AEDC domains, including physical health, emotional maturity, social competence, language/cognitive skills and communication skills/general knowledge. RESULTS: 5051 (71%) Indigenous and 68 998 (74%) non-Indigenous children attended preschool. Among Indigenous children, 33% of preschool attenders and 44% of the home-based care group were vulnerable on ≥1 domains, compared with 17% of preschool attenders and 33% in the home-based care group among non-Indigenous children. In the whole population model, the adjusted risk difference for developmental vulnerability among preschool attenders was -7.9 percentage points (95% CI, -9.8 to -6.1) in non-Indigenous children and -2.8 percentage points (95% CI -4.8 to -0.7) in Indigenous children, compared with Indigenous children in home-based care. CONCLUSIONS: Our findings suggest a likely beneficial effect of preschool participation on developmental outcomes, although the magnitude of the benefit was less among Indigenous compared with non-Indigenous children.
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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 | 0.002 |
| 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".