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Record W2980807325 · doi:10.15126/00852845

Migrant mothers' mental health communication in the perinatal period

2019· article· en· W2980807325 on OpenAlexaboutno aff
Louise Davies, Jasmine Kapoor, D Kowalska, Nadine Page, Ranjana Das, Daniel Beszlag

Bibliographic record

VenueSurrey Research Insight Open Access (The University of Surrey) · 2019
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAgency (philosophy)Quarter (Canadian coin)ImmigrationPhoneMental healthcareQualitative researchPsychologyEthnic groupMedicineFamily medicineGeographySociologyPsychiatrySocial science

Abstract

fetched live from OpenAlex

This report brings together findings from a project on perinatal mental health difficulties amongst migrant mothers, funded by the Wellcome Trust (208437/Z/17/Z), and on early motherhood and digital media, funded by the British Academy (SG151884). Both projects involved interviews with mothers in their homes, with a very small number of them interviewed online. Healthcare professionals were sometimes interviewed on phone. Interviews were qualitative and semi-structured and took the form of free-flowing conversations broadly based on a topic guide. Recruitment through informal channels such as social media and word-of-mouth had limited success and participants recruited through this route accounted for around a quarter of the final set of participants. A recruitment agency was commissioned to administer a door-to-door questionnaire to recruit remaining participants who lived across England, covering mainly the Midlands the South of England and Greater London. Mothers came from a wide range of countries of origin largely in South Asia and Africa and a few from continental Europe. There was a mix of first and second generation immigrants in the final sample. A total of 68 mothers participated across the projects. All participants have been assigned pseudonyms. This report uses selective instances of quotes from interviews to illustrate overall findings and themes.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0050.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.144
GPT teacher head0.448
Teacher spread0.303 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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