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Record W1976737229 · doi:10.3389/fendo.2013.00108

Acculturation, Dietary Acceptability, and Diabetes Management among Chinese in North America

2013· article· en· W1976737229 on OpenAlexaff
Feiyue Deng, Anran Zhang, Catherine B. Chan

Bibliographic record

VenueFrontiers in Endocrinology · 2013
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAcculturationDiabetes mellitusDietary managementMedicineDiabetes managementGerontologyEnvironmental healthGeographyTraditional medicineType 2 diabetesImmigrationInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Immigrants to a new country face many challenges when diagnosed with type 2 diabetes, a chronic disease with a complex treatment involving both medical and behavioral interventions. These challenges will depend upon the extent to which the patient has adapted to the new country's social and cultural norms, as well as individual factors such as age, education, and gender. This adaptation is termed acculturation. With respect to nutritional interventions for type 2 diabetes, uptake and adherence over the long term will depend upon overall health literacy, the cultural acceptability of the recommended diet. This review has focused on acculturation and its effects on diabetes management in ethnic Chinese in North America as an example of one populous minority and the challenges faced in adopting nutritional recommendations. Research directions and practical considerations are suggested.

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)0.001
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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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

Citations43
Published2013
Admission routes1
Has abstractyes

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