International migration to Canada: The post-birth health of mothers and infants by immigration class
Bibliographic record
Abstract
There are over 214 million international migrants worldwide, half of whom are women, and all of them assigned by the receiving country to an immigration class. Immigration classes are associated with certain health risks and regulatory restrictions related to eligibility for health care. Prior to this study, reports of international migrant post-birth health had not been compared between immigration classes, with the exception of our earlier, smaller study in which we found asylum-seekers to be at greatest risk for health concerns. In order to determine whether refugee or asylum-seeking women or their infants experience a greater number or a different distribution of professionally-identified health concerns after birth than immigrant or Canadian-born women, we recruited 1127 migrant (and in Canada <5 years) women-infant pairs, defined by immigration class (refugee, asylum-seeker, immigrant, or Canadian-born). Between February 2006 and May 2009, we followed them from childbirth (in one of eleven birthing centres in Montreal or Toronto) to four months and found that at one week postpartum, asylum-seeking and immigrant women had greater rates of professionally-identified health concerns than Canadian-born women; and at four months, all three migrant groups had greater rates of professionally-identified concerns. Further, international migrants were at greater risk of not having these concerns addressed by the Canadian health care system. The current study supports our earlier findings and highlights the need for case-finding and services for international migrant women, particularly for psychosocial difficulties. Policy and program mechanisms to address migrants' needs would best be developed within the various immigration classes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".