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Record W4245979640 · doi:10.24124/2011/bpgub1506

Role of nurse practitioner in addressing aboriginal diabetes prevention

2011· dissertation· en· W4245979640 on OpenAlexaboutno aff
Douglas Andrew King

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionCommunity healthSocial determinants of healthSocioeconomic statusHealth careNursingMedicineGerontologyPsychologyPublic relationsPolitical scienceEnvironmental healthPublic healthPopulation

Abstract

fetched live from OpenAlex

The current epidemic of Type-2 diabetes among Aboriginal Peoples in Canada has been associated with the poor socioeconomic status of Aboriginal Peoples. Most strategies in diabetes prevention treat health behaviour as an individual choice and ignore how the social determinants of health shape people's health behaviour. The purpose of this project is to explore how NPs might more effectively approach diabetes prevention in Aboriginal communities. This integrative literature review includes a critical analysis of Aboriginal community-based diabetes prevention strategies. A synthesis of their shared characteristics shows that effective community-based diabetes prevention strategies are congruent with primary health care and social justice perspectives on health, which focus on empowering communities and correcting institutionalized discrimination. Community-based strategies empower communities to take control of health promotion efforts and improve community resources and infrastructures that support healthier lifestyles. With an understanding of community-based programs, NPs can begin identifying how primary health care and social justice perspectives can strengthen existing diabetes prevention efforts in Aboriginal communities. --P. i.

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)0.010
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0120.002

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 head0.016
GPT teacher head0.365
Teacher spread0.349 · 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 designQualitative
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

Citations0
Published2011
Admission routes1
Has abstractyes

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