The Lililwan* Project – Prevalence of Fetal Alcohol Spectrum Disorders (FASD) in remote Australian Aboriginal communities.*Lililwan means ‘all of the little ones’ in Kimberley Kriol.
Bibliographic record
Abstract
Background: Prenatal alcohol exposure (PAE) is common in some Australian Aboriginal communities, placing children at risk for Fetal Alcohol Spectrum Disorders (FASD). Aboriginal communities invited researchers to estimate PAE and FASD prevalence among school-aged children. Methods: A population-based study was conducted, using active case-ascertainment. Children born in 2002/2003, living in the Fitzroy Valley, Western Australia during the study period (April 2010–November 2011) were eligible (N=134). Sociodemographic and antenatal data, including PAE, were collected by interview with 127/134 (95%) parents/caregivers. PAE risk levels were determined using the AUDIT-C questionnaire. Neurodevelopmental outcomes were determined through interdisciplinary assessments in 108/134 (81%) children, and FASD diagnoses assigned using modified Canadian FASD diagnostic guidelines. Results: PAE was reported in 55% of pregnancies; 88% in the first trimester, and 53% in all three trimesters. According to AUDIT-C scores, 95% of those who drank did so at risky or high-risk levels. Fetal Alcohol Syndrome (FAS) or partial FAS was diagnosed in 13/108 (120.4 per 1000, 95%CI 70 to 196) children; Neurodevelopmental Disorder-Alcohol Exposed was diagnosed in 8/108 children. Overall prevalence of FASD was 21/108 (194.4 per 1000, 95%CI 131 to 279) children. Conclusions: Rates of high-risk PAE and FASD in this community are among the highest worldwide. Adequate, coordinated, well-resourced child health and education services are imperative to support developmentally vulnerable children in remote communities. Strategies for prevention of PAE and FASD are urgently needed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".