Delivering away from home: the perinatal experiences of First Nations women in northwestern Ontario.
Bibliographic record
Abstract
INTRODUCTION: Our objective was to understand the perinatal knowledge and experiences of First Nations women from northwestern Ontario who travel away from their remote communities to give birth. METHODS: A systematic review of MEDLINE, HealthSTAR, HAPI, Embase, AMED, PsycINFO and CINAHL was undertaken using Medical Subject Headings and keywords focusing on Canadian Aboriginal (First Nations, Metis and Inuit) prenatal education and care, and maternal health literacy. This qualitative study using semistructured interviews was conducted in a rural hospital and prenatal clinic that serves First Nations women. Thirteen women from remote communities who had travelled to Sioux Lookout, Ont., to give birth participated in the study. RESULTS: We identified 5 other qualitative studies that explored the birthing experiences of Aboriginal women. The studies documented a negative experience for women who travelled to access intrapartum maternity care. While in Sioux Lookout to give birth, our participants also experienced loneliness and missed their families. They were open to the idea of a culturally appropriate doula program and visits in hospital by First Nations elders, but they were less interested in access to tele-visitation with family members back in their communities. We found that our participants received most of their prenatal information from family members. CONCLUSION: First Nations women who travel away from home to give birth often travel great cultural and geographic distances. Hospital-based maternity care programs for these women need to achieve a balance of clinical and cultural safety. Programs should be developed to lessen some of the negative consequences these women experience.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".