Birth outcomes among First Nations, Inuit and Métis populations.
Bibliographic record
Abstract
BACKGROUND: First Nations, Inuit, and Métis are at higher risk of adverse birth outcomes than are non-Indigenous people. However, relatively little perinatal information is available at the national level for Indigenous people overall or for specific identity groups. DATA AND METHODS: This analysis describes and compares rates of preterm birth, small-for-gestational-age birth, large-for-gestational-age birth, stillbirth, and infant mortality (neonatal, postneonatal, and cause-specific) in a nationally representative sample of First Nations, Inuit, Métis, and non-Indigenous births. The study cohort consisted of 17,547 births to Indigenous mothers and 112,112 births to non-Indigenous mothers from 2004 through 2006. The cohort was created by linking the Canadian Live Birth, Infant Death and Stillbirth Database to the long form of the 2006 Census, which contains a self-reported Indigenous identifier. RESULTS: With the exception of small-for-gestational-age birth, adverse birth outcomes occurred more frequently among First Nations, Inuit, and Métis women than among non-Indigenous women. Inuit had the highest preterm birth rate (11.4 per 100 births; 95% CI: 9.7 to 13.1) among the three Indigenous groups. The large-for-gestational-age rate was highest for First Nations births (20.9 per 100 births; 95% CI: 19.9 to 21.8). Infant mortality rates were more than twice as high for each Indigenous group compared with the non-Indigenous population, and rates of sudden infant death syndrome were more than seven times higher among First Nations and Inuit. DISCUSSION: The results confirm disparities in birth outcomes between Indigenous and non-Indigenous populations, and demonstrate differences among First Nations, Métis and Inuit.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".