North-South Gradients in Adverse Birth Outcomes for First Nations and Others in Manitoba, Canada~!2009-12-01~!2010-03-31~!2010-07-06~!
Bibliographic record
Abstract
OBJECTIVE: to determine the relationship of north-south place of residence to adverse birth outcomes among First Nations and non-First Nations in Manitoba, Canada, a setting with universal health insurance. STUDY DESIGN: Live birth records (n=151,472) for the province of Manitoba, Canada 1991-2000 were analyzed, including 25,743 First Nations and 125,729 non-First Nations infants. North-south and rural-urban residence was determined for each birth through geocoding. RESULTS: Comparing First Nations to non-First Nations, crude rates in North (and South) were: 7.0% versus 8.4% (9.3% versus 7.5%) for preterm birth; 6.1% versus 8.4% (8.7% versus 10.0%) for small-for-gestational-age birth, 4.2% versus 6.5% (6.2% versus 5.7%) for low birth weight, and 20.6% versus 13.7% (17.0% versus 11.0%) for large-for-gestational-age birth; and mortality per 1000 - neonatal 3.2 versus 6.2 (3.8 versus 3.3), post-neonatal 6.4 versus 6.4 (5.8 versus 1.5), and infant 9.5 versus 12.6 (9.6 versus 4.8). Adjusting for observed maternal and infant characteristics and rural versus urban residence, the North was high risk for large-for-gestational-age birth for both First Nations and non-First Nations. First Nations' risk of preterm, small-for-gestational-age and low birth weight was lowest in the North, but for non-First Nations, the North was lower only for small-for-gestational-age. First Nations mortality indicators were similar North to South, but for non-First Nations, the North was high risk. CONCLUSION: North-South place of residence does matter for adverse birth outcomes, but the effects may differ by ethnicity and could require different intervention strategies.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".