Indigenous Birth Outcomes in Australia, Canada, New Zealand and the United States - an Overview~!2010-01-14~!2010-04-16~!2010-07-06~!
Bibliographic record
Abstract
Objective-To review Indigenous infant mortality, stillbirth, birth weight, and preterm birth outcomes in Australia, Canada, New Zealand and the United States.Methods-Systematic searches of published literature and a review and assessment of existing perinatal surveillance systems were undertaken.Where possible, within country comparisons of Indigenous to non-Indigenous birth outcomes are included.Results-Indigenous/non-Indigenous infant mortality rate ratios range from 1.6 to 4.0.Stillbirth rates, where data are available, are also uniformly higher for Indigenous people.In all four countries, the disparities in Indigenous/non-Indigenous infant mortality rate ratios are most marked in the post-neonatal period.With few exceptions, the rates of leading causes of infant mortality are higher among Indigenous infants than non-Indigenous infants within all four countries.In most cases, rates of small for gestational age and preterm birth were also elevated for Indigenous compared to non-Indigenous infants.Conclusions-There are significant disparities in Indigenous/non-Indigenous birth outcomes in Australia, Canada, New Zealand and the United States.These Indigenous/non-Indigenous birth outcome disparities fit the criteria for health inequities, as they are not only unnecessary and avoidable, but also unfair and unjust.
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 | 0.012 | 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 | 0.013 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".