MétaCan
Menu
Back to cohort
Record W2895355457 · doi:10.1080/01612840.2018.1479903

Immigrant Women and Mental Health Care: Findings from an Environmental Scan

2018· article· en· W2895355457 on OpenAlexafffundabout
Joyce O’Mahony, Nancy Clark

Bibliographic record

VenueIssues in Mental Health Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of VictoriaThompson Rivers University
FundersThompson Rivers University
KeywordsMental healthPostpartum depressionPublic healthImmigrationHealth promotionNursingLanguage barrierMedicinePsychologyGerontologyPsychiatryPolitical sciencePregnancy

Abstract

fetched live from OpenAlex

Immigrant women's mental health is a growing public health policy issue. New immigrant mothers may be particularly vulnerable to less than optimal mental health following childbirth given the cultural and geographic isolation, socioeconomic factors, gender roles, and language difficulties that influence their postpartum experiences. The purpose of this environmental scan was to increase understanding of immigrant women's perinatal mental health care services within the interior of a western Canadian province. Four interrelated themes emerged to impact postpartum health of immigrant women: (i) community capacity building, (ii) facilitators of mental health support and care, (iii) barriers of mental health promotion and support, and (iv) public policy and postpartum depression. Knowledge gained from this study contributes to healthy public policy and practices that promote mental health and support among immigrant women.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.758
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.343
Teacher spread0.332 · 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 source (direct Gemma or distilled Codex), 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

Citations39
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueIssues in Mental Health NursingSame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207