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Record W2976496861

Prevention and Healthcare Promotion for Children and Young Persons: Description and Stakes of Being a Community Nurse in Canada

2004· article· en· W2976496861 on OpenAlexaboutno aff
Lionel Richard, Sylvie Fortin, F. Bérubé

Bibliographic record

VenueSante Publique · 2004
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionPromotion (chess)Intervention (counseling)NursingWork (physics)Health careDisease preventionAction (physics)MedicinePsychologyPublic relationsPolitical sciencePublic healthEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

This article aims to provide an overview of the disease prevention and health promotion work carried out by CLSC nurses working with infants, children and youth. A second objective is to present our synthesis of four recent studies on the state of prevention-promotion in these organizations. This is followed by our analysis of several contemporary issues related to nursing practice in this intervention sector. While disease prevention and health promotion is a major component of the practice of CLSC nurses who work with infants, children and youth, it is an intervention sector that has been weakened by numerous changes affecting these organizations in the wake of the reform. The discussion thus proposes several courses of research and action in the hopes of strengthening this major component of the CLSC mission.

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)0.004
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: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0110.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.383
Teacher spread0.329 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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