320 Perinatal health inequalities and migration: experiences, barriers and support for women in precarious circumstances in Canada
Bibliographic record
Abstract
Abstract WKS 26: Perinatal Health Inequalities and Migration: Experiences, Barriers and Support for Women in Precarious Circumstances in Canada, B309 (FCSH), September 5, 2025, 09:00 - 10:00 Rationale and Purpose In Canada, childbearing im/migrant women may face increased vulnerability due to a precarious migration status (asylum seekers, temporary workers, undocumented), cultural and linguistic barriers, or due to challenging socioeconomic conditions. Some have also experienced traumatic migration trajectories, contributing to complex and often unmet health needs. Im/migrant women frequently encounter difficulties when accessing perinatal care, including systemic obstacles within the healthcare system. Drawing from various research studies, this workshop examined the distinct perinatal health and care challenges experienced by im/migrant women in vulnerable circumstances in Québec, Canada and engaged participants in a discussion on actionable strategies aimed at reducing inequalities and promoting health and wellbeing throughout pregnancy, childbirth and postpartum. Workshop The first part of the workshop focused on uninsured migrant women, critically examining the repercussions of pregnancy without legal status, including restricted access to care, significant financial hardship, and adverse effects on family relationships and education/professional aspirations. Key policy recommendations aimed at mitigating these inequities, were also addressed. The second half examined the perinatal care experiences of recently arrived migrant women from non-Western countries, emphasizing their perceptions of healthcare providers, access to prenatal care, and encounters with communication facilitation and responsive care. Associations between key socioeconomic and migratory determinants and specific aspects of maternity care, were also presented. Learning Outcomes
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".