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Record W4400775893 · doi:10.3389/fnut.2024.1420323

Food environment in Burkina Faso: priority actions recommended to the government using Food-EPI tool

2024· article· en· W4400775893 on OpenAlexfundno aff
Viviane Aurelie Tapsoba, Ella W. R. Compaoré, Augustin Nawidimbasba Zeba, Jérôme W. Somé, Julien Soliba Manga, Jean‐Claude Moubarac, Stefanie Vandevijvere, Mamoudou H. Dicko

Bibliographic record

VenueFrontiers in Nutrition · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNutrition, Health, and Society Studies
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsGovernment (linguistics)BusinessPromotion (chess)Food safetyMalnutritionPopulationSustainabilityHealthy foodFood systemsSustainable agricultureMarketingEconomic growthPoliticsEnvironmental healthFood securityPolitical scienceMedicineAgricultureGeographyEconomics

Abstract

fetched live from OpenAlex

Introduction: The food environment is an important factor in the efforts of countries worldwide to achieve a transition to sustainable food systems. The objective of this study is to formulate and prioritize actions to be addressed to the government of Burkina Faso for the creation of a healthy food environment, which will contribute to reducing malnutrition in all its forms and non-communicable diseases. Methods: National experts were brought together to identify and prioritize actions to fill the gaps identified through a multi-step assessment process following the methodology of the Healthy Food and Environment Policy Index (Food-EPI). Results: Up to 20 priority policy actions were recommended to the Burkina Faso government. Actions in the policy component focused mainly on regulation of food promotion and marketing, particularly to children, and others in the infrastructure support component focused largely on political leadership, i.e., strong and visible political support from the government to improve the food environment, population nutrition, diet-related non-communicable diseases and their inequalities. Conclusion: The priority actions to be recommended to the government will strengthen advocacy for government decisions to create a healthier food environment in the country.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.245
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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