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Record W2013718825 · doi:10.1108/13660750210441884

A conceptual model for a culturally responsive community‐based diabetes prevention programme

2002· article· en· W2013718825 on OpenAlexaffabout
Shirley Wong, Julia Wong, Lydia Makrides, Swarna Weerasinghe

Bibliographic record

VenueLeadership in Health Services · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSociocultural evolutionConceptual frameworkConceptual modelCulturally appropriatePublic healthCulturally sensitiveGerontologyThe Conceptual FrameworkType 2 diabetesDiabetes mellitusMedicinePsychologySociologyNursingSocial psychologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Type 2 diabetes mellitus has emerged as a major public health problem in Canada. Although the prevalence of Type 2 diabetes among black people is higher than that of white people in Canada, there is no diabetes prevention programme specifically designed to address the behavioural and sociocultural influences on the development of the disease in the black communities. This paper discusses a proposed conceptual framework for the development and evaluation of a diabetes prevention programme that is culturally relevant and responsive to the black communities in Canada. The research literature and results of a recent pilot study that assessed the programming needs of four black communities provide the basis upon which the proposed framework is developed.

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)0.017
metaresearch head score (Gemma)0.010
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.016
Scholarly communication0.0090.007
Open science0.0040.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.877
GPT teacher head0.616
Teacher spread0.261 · 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

Citations6
Published2002
Admission routes2
Has abstractyes

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