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Record W2150686951 · doi:10.1177/019394590102300405

Uprooting and Resettlement Experiences of South Asian Immigrant Women

2001· article· en· W2150686951 on OpenAlexaffabout
U.K. Choudhry

Bibliographic record

VenueWestern Journal of Nursing Research · 2001
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLonelinessImmigrationCoping (psychology)Qualitative researchSocial isolationPsychologyAcculturationSocial supportIndependence (probability theory)Health careNursingSocial psychologyGerontologySociologyMedicineClinical psychologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

The purpose of this descriptive qualitative study was to examine and understand the challenges faced by elderly women from India who immigrated to Canada. Ten women were interviewed about their experiences with immigration and resettlement. The analysis of interview data involved iterative process, through which four themes were identified. These themes were isolation and loneliness, family conflict, economic dependence, and setting in and coping. The participants experienced loss because of changes in traditional values and lack of social support. Because the participants could not manage resettlement on their own, personal independence was not very important. Interdependence for the attainment of emotional security and social rewards was more desirable. Health care professionals must take into account the nature of stress and impact of these experiences on health of older 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0020.001
Open science0.0010.004
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 head0.119
GPT teacher head0.469
Teacher spread0.350 · 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 designQualitative
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

Citations141
Published2001
Admission routes2
Has abstractyes

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