The childbearing health and related service needs of newcomers (CHARSNN) study protocol
Bibliographic record
Abstract
BACKGROUND: Refugee and asylum-seeking women in Canada may have significant harmful childbearing health outcomes and unmet health and social care needs. The most vulnerable of these women are: those who have left their countries by force (e.g., war, rape or abuse histories), are separated from their families, have limited knowledge of the host country languages, and are visible minorities. Asylum-seekers face additional stresses related to their unknown future status and are marginalized with regards to access to provincial health care systems. The prevalence and severity of health issues in this population is not known nor is the extent of response from social service and health care systems (including variation in provincial service delivery). Understanding the magnitude of health and social concerns of newcomers requires data from a representative sample of childbearing refugee and asylum-seeking women resettling in Canada to permit comparisons to be made with non-refugee immigrant and Canadian-born women. Our research questions are: (1) Do refugee or asylum-seeking women and their infants, experience a greater number or a different distribution of harmful health events during pregnancy, at birth, and during the postpartum period than non-refugee immigrant or Canadian-born women? (2) Are the harmful health events experienced postpartum by asylum-seeking women and their infants, addressed less often (compared to refugees, non-refugee immigrants, and Canadian-born women) by the Canadian health care system as delivered in each of the three major receiving cities for newcomers? METHODS/DESIGN: This is a four-year multi-site prospective cohort study (pregnancy to 4 months postpartum). We will seek to recruit 2400 women [200 in each of 4 groups (refugees, asylum-seekers, non-refugee immigrants, and Canadian-born) from 1 of 12 postpartum hospital units across the 3 largest receiving cities for newcomers to Canada - Montreal, Toronto, and Vancouver]. DISCUSSION: Knowledge of the extent of harmful health events occurring to asylum-seeking, refugee, immigrant, and Canadian-born women, and the response of the health care system to those events and group differences, if they exist, will inform immigration and health policy makers as well as providers of services.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
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".