Primary birthing attendants and birth outcomes in remote Inuit communities—a natural “experiment” in Nunavik, Canada
Bibliographic record
Abstract
BACKGROUND: There is a lack of data on the safety of midwife-led maternity care in remote or indigenous communities. In a de facto natural "experiment", birth outcomes were assessed by primary birthing attendant in two sets of remote Inuit communities. METHODS: A geocoding-based retrospective birth cohort study in 14 Inuit communities of Nunavik, Canada, 1989-2000: primary birth attendants were Inuit midwives in the Hudson Bay (1529 Inuit births) vs western physicians in Ungava Bay communities (1197 Inuit births). The primary outcome was perinatal death. Secondary outcomes included stillbirth, neonatal death, post-neonatal death, preterm, small-for-gestational-age and low birthweight birth. Multilevel logistic regression was used to obtain the adjusted odds ratios (aOR) controlling for maternal age, marital status, parity, education, infant sex and plurality, community size and community-level random effects. RESULTS: The aORs (95% confidence interval) for perinatal death comparing the Hudson Bay vs Ungava Bay communities were 1.29 (0.63 to 2.64) for all Inuit births and 1.13 (0.48 to 2.47) for Inuit births at > or =28 weeks of gestation. There were no statistically significant differences in the crude or adjusted risks of any of the outcomes examined. CONCLUSION: Risks of perinatal death were somewhat but not significantly higher in the Hudson Bay communities with midwife-led maternity care compared with the Ungava Bay communities with physician-led maternity care. These findings are inconclusive, although the results excluding extremely preterm births are more reassuring concerning the safety of midwife-led maternity care in remote indigenous communities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".