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Record W2010894644 · doi:10.1177/0898264308328636

Chinese Health Beliefs of Older Chinese in Canada

2009· article· en· W2010894644 on OpenAlexaffabout
Daniel W. L. Lai, Shireen Surood

Bibliographic record

VenueJournal of Aging and Health · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsChinese peopleDiversity (politics)Sociocultural evolutionExploratory researchTelephone surveyPsychologyChinaTelephone interviewMedicineCultural diversityFamily medicineGerontologySociologyAdvertisingGeography

Abstract

fetched live from OpenAlex

Objectives. This study examines the cultural health beliefs held by older Chinese in Canada. Methods. Chinese surnames are randomly selected from the local Chinese telephone directories. Telephone screening is then conducted to identify eligible Chinese people 55 years of age or older to take part in a face-to-face interview to complete a structured survey questionnaire. Results. The results of exploratory factor analysis indicate that the health beliefs of the older Chinese are loaded onto three factors related to beliefs about traditional health practices, beliefs about traditional Chinese medicine, and beliefs about preventive diet. Education, religion, country of origin, length of residency in Canada, and city of residency are the major correlates of the various Chinese health beliefs scales. Discussion. The findings support the previous prescriptive knowledge about Chinese health beliefs and illustrate the intragroup sociocultural diversity that health practitioners should acknowledge in their practice.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.383
Teacher spread0.360 · 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

Citations77
Published2009
Admission routes2
Has abstractyes

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