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Record W7000470252

"Female Newcomers’ Adjustment to Life in Toronto, Canada: Sources of Stress and Their Implications for Delivering Primary Mental Health Care"

2011· article· en· W7000470252 on OpenAlexfundaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2011
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersLupina Foundation
KeywordsMental healthThematic analysisStress (linguistics)Primary careHealth careMental health careMetropolitan areaPrimary health care
DOInot available

Abstract

fetched live from OpenAlex

Stress disorders and other mental ill health may be brought on by the disruption caused by resettlement. We examine female newcomers' experiences of adjusting to a new place, metropolitan Toronto, Canada and a new health care system. We consider sources of mental stress experienced during adjustment. We frame this adjustment as a process that happens over place and through time. Thematic findings of interviews (n = 35) with female newcomers from five cultural-linguistic groups are reported. Sources of stress in adjusting to life in Toronto include: navigating a new place, personal safety concerns, adapting to a new lifestyle, and finding employment. Sources of stress in adjusting to a new health care system include: learning how to access care, not having access to specialists, and adapting to a new culture of care. We conclude by considering the implications of what newcomers report for the delivery of primary mental health care (i.e. 'first contact' care).

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0170.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
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 head0.022
GPT teacher head0.213
Teacher spread0.191 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueYork University Digital Library (York University)→Same topicMigration, Health and Trauma→French-language works237,207→