Navigating maternity health care: a survey of the Canadian prairie newcomer experience
Bibliographic record
Abstract
BACKGROUND: Immigration to Canada has significantly increased in recent years, particularly in the Prairie Provinces. There is evidence that pregnant newcomer women often encounter challenges when attempting to navigate the health system. Our aim was to explore newcomer women's experiences in Canada regarding pregnancy, delivery and postpartum care and to assess the degree to which Canada provides equitable access to pregnancy and delivery services. METHODS: Data were obtained from the Canadian Maternity Experiences Survey. Women (N = 6,241) participated in structured computer-assisted telephone interviews. Women from Alberta, Saskatchewan and Manitoba were included in this analysis. A total of 140 newcomers (arriving in Canada after 1996) and 1137 Canadian-born women met inclusion criteria. RESULTS: Newcomers were more likely to be university graduates, but had lower incomes than Canadian-born women. No differences were found in newcomer ability to access acceptable prenatal care, although fewer received information regarding emotional and physical changes during pregnancy. Rates of C-sections were higher for newcomers than Canadian-born women (36.1% vs. 24.7%, p = 0.02). Newcomers were also more likely to be placed in stirrups for birth and have an assisted birth. CONCLUSION: Although newcomers residing in Prairie Provinces receive adequate maternity care, improvements are needed with respect to provision of information related to postpartum depression and informed choice around the need for C-sections.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".