Remote Midwifery in Nunavik, Québec, Canada: Outcomes of Perinatal Care for the Inuulitsivik Health Centre, 2000–2007
Bibliographic record
Abstract
BACKGROUND: The Inuulitsivik midwifery service is a community-based, Inuit-led initiative serving the Hudson coast of the Nunavik region of northern Québec. This study of outcomes for the Inuulitsivik birth centers, aims to improve understanding of maternity services in remote communities. METHODS: We used a retrospective review of perinatal outcome data collected at each birth at the Inuulitsivik birth centers to examine outcomes for 1,372 labors and 1,382 babies from 2000 to 2007. Data were incomplete for some indicators, particularly for transfers to Montreal. RESULTS: Findings revealed low rates of intervention with safe outcomes in this young, largely multiparous "all risk" Inuit population. Ninety-seven percent of births were documented as spontaneous vaginal deliveries, and 85 percent of births were attended by midwives. Eighty-six percent of the labors occurred in Nunavik, whereas 13.7 percent occurred outside Nunavik. The preterm birth rate was found to be 10.6 percent. Postpartum hemorrhage was documented in 15.4 percent of women; of these cases, 6.9 percent had blood loss greater than 1,000 mL. Four fetal deaths (2.9 per 1,000) and five neonatal deaths (< 3.6 per 1,000) were documented. Nine percent (9%) of births involved urgent transfers of mother or baby. The most common reasons for medical evacuation were preterm labor and preeclampsia, and preterm birth was the most common reason for urgent neonatal transfer. CONCLUSIONS: The success of the Innulitsivik midwifery service rests on the knowledge and skills of the Inuit midwives, and support of an interprofessional health team. Our study points to the potential for safe, culturally competent local care in remote communities without cesarean section capacity. Our findings support recommendations for integration of midwifery services and Aboriginal midwifery education programs in remote 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".