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Record W2025147919 · doi:10.1177/0193945903256709

The Politics of Belonging and Intercultural Health Care

2003· article· en· W2025147919 on OpenAlexaff
Sheryl Reimer‐Kirkham

Bibliographic record

VenueWestern Journal of Nursing Research · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsPoliticsPsychologySociologyNursingMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

Belonging was one of the recurrent themes in an ethnography examining the social context of intergroup health care relations. Certain people, both patients and health care providers, were constructed as belonging in the social fabric of health care, whereas some were left on the margins and constructed as Other. In this article, the theme of belonging is explored through a multilayered analysis of the contexts of intergroup health care encounters. The macropolitics of belonging are situated in the larger societal setting, replete with practices that mark Other. Evidences of such Othering is then traced through organizational contexts, drawing on the exemplars of visiting hour policy, integration of alternative therapies, and provision of language services. Intergroup interactions are then reanalyzed in light of micropolitics at the individual nurse-patient level. The overall picture presented is one of a range of social, political, historical, and economic forces reproduced in everyday intercultural health care encounters.

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)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0260.085
Scholarly communication0.0110.008
Open science0.0010.015
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.131
GPT teacher head0.508
Teacher spread0.377 · 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 designTheoretical or conceptual
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

Citations73
Published2003
Admission routes1
Has abstractyes

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