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Record W2127621308 · doi:10.1177/104973230201200603

Immigrant Women: Making Connections to Community Resources for Support in Family Caregiving

2002· article· en· W2127621308 on OpenAlexaff
Anne Neufeld, Margaret J. Harrison, Miriam J. Stewart, Karen D. Hughes, Denise L. Spitzer

Bibliographic record

VenueQualitative Health Research · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsCanadian Institutes of Health ResearchInstitute of Gender and HealthUniversity of Alberta
Fundersnot available
KeywordsOutreachImmigrationSocial supportService (business)EthnographyCommunity serviceNursingPsychologyMedicineSociologyPublic relationsSocial psychologyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

The purpose of this ethnographic study was to understand how immigrant women caregivers accessed support from community resources and identify the barriers to this support. The study included 29 Chinese and South Asian women caring for an ill or disabled child or adult relative. All experienced barriers to accessing community services. Some possessed personal resources and strategies to overcome them; others remained isolated and unconnected. Family and friends facilitated connections, and a connection with one community service was often linked to several resources. Caregivers who failed to establish essential ties could not initiate access to resources, and community services lacked outreach mechanisms to identify them. These findings contribute new understanding of how immigrant women caregivers connect with community resources and confirm the impact of immigration on social networks and access to 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 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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0020.002
Open science0.0000.003
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 head0.398
GPT teacher head0.559
Teacher spread0.161 · 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

Citations156
Published2002
Admission routes1
Has abstractyes

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