Mothering Here and Mothering There: International Migration and Postbirth Mental Health
Bibliographic record
Abstract
Over 125,000 women immigrate to Canada yearly-most in their childbearing years and many having given birth before immigrating. We sought to (1) examine the background characteristics and mental health profile of women separated from their children due to migration and subsequently giving birth in Canada ("dual-country (DC) mothers") and (2) contrast these with those of "non-dual-country" migrant mothers. Of 514 multiparous migrant women giving birth, one-fifth (18%) reported being separated from their children due to migration. Over one-third of DC mothers were living in poverty (36.0% versus 18.6%, P = 0.001), and one in seven was experiencing household food insecurity (16.3% versus 7.6%, P = 0.01). Over one-third had no partner (40.2% versus 11.4%, P = 0.00), and nearly one-quarter reported no available support (23.1% versus 12.2%, P = 0.007). Over three-quarters were asylum seekers or refugees (83.7% versus 51%, P = 0.00). More DC than non-DC mothers had symptoms of postpartum depression (28.3% versus 18.6%, P = 0.04), symptoms of clinical depression (23.1% versus 13.5%, P = 0.02), and anxiety related to trauma (16.5% versus 9.4%, P = 0.04). Results suggest that identifying DC mothers is a rapid approach to enable clinicians to target a subgroup of women needing special attention.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".