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Record W2155529804 · doi:10.1017/s000711451400230x

Beyond nutrition and agriculture policy: collaborating for a food policy

2014· article· en· W2155529804 on OpenAlexafffund
Derek A. Stewart, Anne F. Kennedy, Anthony Pavel

Bibliographic record

VenueBritish Journal Of Nutrition · 2014
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsAgriculture and Agri-Food Canada
FundersBiotechnology and Biological Sciences Research CouncilGovernment of CanadaAgriculture and Agri-Food CanadaJames Hutton InstituteRural and Environment Science and Analytical Services DivisionDepartment for Environment, Food and Rural Affairs, UK GovernmentPepsiCo
KeywordsAgricultureFood industryGovernment (linguistics)BusinessPopulation ageingFood systemsPopulationFood safetyFood policyFood supplyMarketingPublic economicsEconomicsFood securityAgricultural economicsPolitical scienceEnvironmental healthMedicineGeography

Abstract

fetched live from OpenAlex

Global interest in food policy is emerging in parallel with mounting challenges to the food supply and the rising prevalence of diet-related chronic health conditions. Some of the foundational elements of food policies are agricultural practices, finite resources, as well as economic burdens associated with a growing and ageing population. At the intersection of these interests is the need for policy synchronisation and a better understanding of the dynamics within local, regional and national government decision-making that ultimately affect the wellness of the populous and the safety, quality, affordability and quantity of the food supply. Policies, synchronised or not, need to be implemented and, for the food industry, this has seen a myriad of approaches with respect to condensing complex nutritional information and health claims. These include front and/or back of pack labelling, traffic light systems, etc. but in general there is little uniformity at the more regional and global scales. This translation of the nutritional and health-beneficial messages accompanying specific products to the consumer will undoubtedly be an area of intense activity, and hopefully interaction with policy makers, as the food industry continues to become a more global industry.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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 designOther design
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

Citations16
Published2014
Admission routes2
Has abstractyes

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