“I felt so alone in the process:” Experiences of Indigenous women with maternal medical travel in the Canadian Arctic and opportunities for improvement
Bibliographic record
Abstract
PROBLEM: Indigenous women face unique challenges during pregnancy/birth-related medical travel due to systemic barriers, cultural differences, and geographic isolation. BACKGROUND: In Canada, Indigenous women frequently travel substantial distances for pregnancy care and birth. Many pregnant women in Northwest Territories (NWT) are mandated to travel to urban centres with secondary/tertiary hospitals between 36-38-weeks gestation. QUESTION/HYPOTHESIS/AIM: What are the experiences of Indigenous women in NWT regarding pregnancy and birth-related medical travel? How do cultural and community-specific, culturally informed, and accessible healthcare practices influence the experiences of Indigenous women during pregnancy-related medical travel? METHODS: Across three NWT communities, 156 self-identifying Indigenous women who were pregnant or who had given birth in the previous three years completed a semi-structured interviewer-administered questionnaire. Qualitative data were analyzed using reflexive thematic analysis in NVivo. FINDINGS: Of the 55 women who travelled for pregnancy care, 68.5 % felt prepared for medical travel and 57.4 % had a positive experience. Of the 52 women who travelled for birth, the mean length of stay after birth was 11 days (ranges from 1 to 90 days), with 63.5 % staying ≤ one week. PARTICIPANTS HIGHLIGHTED THREE THEMES: Travel experiences, experiences with prenatal care and childbirth, and suggestions for improvement. The experiences involved loneliness, nervousness, logistical challenges, and communication and resource issues. DISCUSSION: Suggestions included improving cultural competency, expanding community healthcare, and incorporating Elder knowledge sharing. CONCLUSION: While many women reported positive experiences, improvements in medical travel and care access are needed to guide Indigenous maternal healthcare policy and planning.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.056 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".