Does Living On-Reserve Versus Off-Reserve Make a Difference in First Nations Birth Outcomes in Manitoba, Canada?
Bibliographic record
Abstract
Objective: First Nations people in Canada often migrate between living “on-reserve” and “off-reserve.” The purpose of this study was to determine if there was any difference in birth outcomes among First Nations women living on-reserve versus off-reserve in Manitoba. Study Design: This population-based birth cohort study was conducted using Statistics Canada’s linked vital data for Manitoba, 1991-2000. A total of 26,176 First Nation births were identified (14,165 on-reserve, 12,011 off-reserve), based on self reporting by the mother or father. A mother was considered to be living on-reserve if her residential postal code (or municipal code) was among those used for First Nations bands or communities. Results: The crude rates of preterm (7.5% versus 9.7%) and small-for-gestational-age (7.3% versus 8.1%) births were significantly lower among First Nations women living on-reserve compared to off-reserve, while rates of neonatal death (4.1 versus 4.1 per 1,000) and postneonatal death (6.6 versus 5.6 per 1,000) were not significantly different. After adjusting for maternal characteristics and rural versus urban residence, the lower risks of preterm birth (adjusted odds ratio [aOR] 0.82 [95% confidence interval [CI] 0.75-0.90]) and small-for-gestational-age (aOR 0.89 [0.81-0.98]) on-reserve remained, but a higher risk of infant death was observed (aOR 1.29, 95% CI 1.00-1.67) mostly due to higher risk of postneonatal death. Conclusion: Living off-reserve is associated with higher rates of preterm and small-for-gestational-age births, suggesting the need to improve prenatal care. Living on-reserve is associated with higher rates of infant death, suggesting the need to improve infant care and socioeconomic conditions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".