PRENATAL HEALTHCARE AMONG IMMIGRANT MOTHERS IN CANADA: AN EXPLORATION OF BARRIERS TO ADEQUATE AND CULTURALLY COMPETENT CARE
Bibliographic record
Abstract
Immigrants in Canada make up more than 20% of the population and are quite diverse, many migrating under the economic category to amplify economic development (Statistics Canada, 2017a). Despite the growing number of immigrants in the country, there remain gaps in culturally competent and adequate care for immigrant mothers who live in Canada. This thesis examined prenatal care barriers experienced by immigrant mothers in Canada. First, a systematic scoping review was undertaken. A total of 17 studies were included and analyzed. Cultural and institutional factors affected mothers’ access to and perception of prenatal care in the Canadian healthcare system. Second, an online survey was conducted with immigrant women in Saskatchewan who had received prenatal care within the past 3 years (N=70) between September 2021 and March 2022. This included participants from Africa (n=56), Asia (n=9), Europe (n=2), North America (n=2), and South America (n=1). 15.71% of the participants were pregnant when completing the survey. Factors such as transportation, no health problems, affordability of prenatal care, and social support increased participants’ access to prenatal care, while work schedules and COVID-19 had the opposite effect.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".