Long-distance travel for birthing among Indigenous and non-Indigenous pregnant people in Canada
Bibliographic record
Abstract
BACKGROUND: For Indigenous Peoples in Canada, birthing on or near traditional territories in the presence of family and community is of foundational cultural and social importance. We aimed to evaluate the association between Indigenous identity and distance travelled for birth in Canada. METHODS: We obtained data from the Maternity Experiences Survey, a national population-based sample of new Canadian people aged 15 years or older who gave birth (defined as mothers) and were interviewed in 2006-2007. We compared Indigenous with non-Indigenous Canadian-born mothers and adjusted for geographic and sociodemographic factors and medical complications of pregnancy using multivariable logistic regression. We categorized the primary outcome, distance travelled for birth, as 0 to 49, 50 to 199 or 200 km or more. RESULTS: We included 3100 mothers living in rural or small urban areas, weighted to represent 31 100 (1800 Indigenous and 29 300 non-Indigenous Canadian-born mothers). We found that travelling 200 km or more for birth was more common among Indigenous compared with non-Indigenous mothers (9.8% v. 2.0%, odds ratio [OR] 5.45, 95% confidence interval [CI] 3.52-8.48). In adjusted analyses, the association between Indigenous identity and travelling more than 200 km for birth was even stronger (adjusted OR 16.44, 95% CI 8.07-33.50) in rural regions; however, this was not observed in small urban regions (adjusted OR 1.04, 95% CI 0.37-2.91). INTERPRETATION: Indigenous people in Canada experience striking inequities in access to birth close to home compared with non-Indigenous people, primarily in rural areas and independently of medical complications of pregnancy. This suggests inequities are rooted in the geographic distribution of and proximal access to birthing facilities and providers for Indigenous people.
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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 | 0.001 |
| 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".