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Record W2059194386 · doi:10.1155/2012/593413

Mothering Here and Mothering There: International Migration and Postbirth Mental Health

2012· article· en· W2059194386 on OpenAlexafffundabout
Stephanie S. Bouris, Lisa Merry, Amy Kebe, Anita J. Gagnon

Bibliographic record

VenueObstetrics and Gynecology International · 2012
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill University Health CentreUniversité Sainte-AnneMcGill University
FundersCanadian Institutes of Health ResearchInstitut National de la Santé et de la Recherche MédicaleMcGill University Health CentreMcGill University
KeywordsMedicineMental healthRefugeeAnxietyPovertyDepression (economics)Quarter (Canadian coin)DemographyFood insecurityPsychiatryFood securityGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.291
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2012
Admission routes3
Has abstractyes

Explore more

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