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Record W1996057296 · doi:10.1079/phn2005777

Public('s) nutrition

2005· review· en· W1996057296 on OpenAlexaff
Micheline Beaudry, Hélène Delisle

Bibliographic record

VenuePublic Health Nutrition · 2005
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicNutrition, Health, and Society Studies
Canadian institutionsUniversité de MontréalUniversité Laval
Fundersnot available
KeywordsPublic healthMalnutritionHealth promotionFood securityNutrition EducationPopulationPromotion (chess)Action (physics)Public relationsEnvironmental healthPolitical scienceMedicineGerontologyNursingBiologyAgriculture

Abstract

fetched live from OpenAlex

OBJECTIVE: To promote the new field of 'public nutrition' as a means to address, in a more efficient, sustainable and ethical manner, the world-wide epidemic of malnutrition--undernutrition and specific nutrient deficiencies, and also obesity and other nutrition-related chronic diseases. STRATEGY: Grounded in the health promotion model, public nutrition applies the population health strategy to the resolution of nutrition problems. It encompasses 'public health nutrition', 'community nutrition' and 'international nutrition' and extends beyond them. It fits within the conceptual framework of 'the new nutrition science' and is an expression of this reformulated science in practice. Its fundamental goal is to fulfil the human right to adequate food and nutrition. It is in the interest of the public, it involves the participation of the public and it calls for partnerships with other relevant sectors beyond health. Public nutrition takes a broader view of nutritional health, addressing the three interrelated determinant categories of food systems and food security; food and health practices; and health systems. It assesses and analyses how these influence the immediate determinants that are dietary intake and health status so as to direct action towards effective progress. To further enhance the relevance and effectiveness of action, public nutrition advocates improved linkages between policies and programmes, research and training. A renewed breed of professionals for dietetics and nutrition, trained along those lines, is suggested. CONCLUSION: There is a critical need to develop new knowledge, approaches and skills to meet the pressing nutrition challenges of our times.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.907
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.222
GPT teacher head0.359
Teacher spread0.136 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2005
Admission routes1
Has abstractyes

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