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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".