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Record W2313565721 · doi:10.1097/ans.0b013e3182300d9a

Advancing Population-Based Health-Promotion and Prevention Practice in Community-Health Nursing

2011· article· en· W2313565721 on OpenAlexaffabout
Nicole Beaudet, Lucie Richard, Sylvie Gendron, Nancy Boisvert

Bibliographic record

VenueAdvances in Nursing Science · 2011
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHealth promotionNursingOccupational health nursingCommunity healthPopulationPromotion (chess)Work (physics)Population healthAction (physics)MedicineHealth educationPublic healthPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

In Brief Community-health nursing practice is a pivotal aspect of present-day health reforms. In Quebec, Canada, the recent introduction of a population-based approach has entailed increasing the resources allocated to health promotion and disease prevention. Semistructured interviews were conducted with nurses and managers (N = 69) in an effort to understand how these new resources are reflected in nursing practice. Three classes of factors emerged as key conditions for change: contextual and historical, training and professional-development, and work-organization factors. The authors propose courses of action respecting these conditions to provide support for community-health nursing practices that incorporate a contemporary population-based approach. Semi-structured interviews were conducted with nurses and managers (N = 69) in an effort to understand how the new resources allocated to health promotion and disease prevention in Quebec, Canada, are reflected in nursing practice. Three classes of factors emerged as key conditions for change: contextual and historical, training and professional-development, and work-organization factors. www.advancesinnursingscience.com

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.002
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 head0.070
GPT teacher head0.526
Teacher spread0.456 · 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.

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

Citations25
Published2011
Admission routes2
Has abstractyes

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