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Record W2171593263 · doi:10.1177/0193945906296431

Chinese Immigrants' Management of Their Cardiovascular Disease Risk

2007· article· en· W2171593263 on OpenAlexaffabout
Kathryn King, Pamela LeBlanc, W. Amory Carr, Hude Quan

Bibliographic record

VenueWestern Journal of Nursing Research · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGrounded theoryImmigrationDiligenceDiseaseMedicinePsychologyDue diligenceInterpreterGerontologyQualitative researchSocial psychologySociologyComputer scienceGeographyPolitical sciencePathology

Abstract

fetched live from OpenAlex

The authors have undertaken a series of grounded theory studies to describe and explain how ethnocultural affiliation and gender influence the process that cardiac patients undergo when faced with making behavior changes associated with reducing their cardiovascular disease (CVD) risk. Data were collected through audiorecorded semistructured interviews (using an interpreter as necessary), and the authors analyzed the data using constant comparative methods. The core variable that emerged through the series of studies was "meeting the challenge." Here, the authors describe the findings from a sample of Chinese immigrants (10 men, 5 women) to Canada. The process of managing CVD risk for the Chinese immigrants was characterized by their extraordinary diligence in seeking multiple sources of information to enable them to manage their health.

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)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.452
Teacher spread0.391 · 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

Citations29
Published2007
Admission routes2
Has abstractyes

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