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Record W2252632793

Social support and health: immigrants and refugees perspectives

2010· article· en· W2252632793 on OpenAlexaboutno aff
Edward Makwarimba, Miriam J. Stewart, Morton Beiser, Anne Neufeld, Laura Simich, Denise L. Spitzer

Bibliographic record

VenueDiversity & Equality in Health and Care · 2010
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSomaliSocial supportMental healthRefugeeLonelinessImmigrationPsychologySocial psychologyPolitical sciencePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Migration and integration are linked to depleted support networks. Although social support is a key determinant of health, newcomers’ appraisal of social support and its impact on health have not been adequately studied. This investigation focused on immigrants’ and refugees’ views of social support, its perceived influence on health and the use of health-related services. Individual in-depth interviews were conducted with 60 Chinese immigrants and 60 Somali refugees in Canada. The study revealed many stressful situations, including health problems that signified a need for support. Just as inadequateand inappropriate support has a negative impact on health, poor health can diminish available support. Social support facilitated employment and ability to meet basic needs, reduced stress, and improved physical and mental health. Support from others reduced loneliness and despair and enhanced the mental health of newcomers. Newcomers believedthat inadequate support exerted a negative influence on their health and use of health-related services, and that poor health had a detrimental effect on the ability to seek or offer support.

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)0.001
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 score0.271
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.060
GPT teacher head0.400
Teacher spread0.340 · 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

Citations40
Published2010
Admission routes1
Has abstractyes

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