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Agri‐Food Governance and Expertise: The Production of International Food Standards

2009· article· en· W2010801586 on OpenAlexaff
Richard Lee

Bibliographic record

VenueSociologia Ruralis · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsCorporate governanceFood processingProcess (computing)CommissionProduction (economics)Food systemsSet (abstract data type)Political scienceBusinessEconomicsAgricultureFood securityManagementLawEcologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Abstract This article examines a particular mode of agri‐food governance: international food standard setting. Sociological accounts of technical regulatory processes such as standard setting can help to illuminate the role of expertise in the governance of the agri‐food system. Firstly, the potential contribution of the concept of epistemic communities to the analysis of international food standard setting is discussed. Secondly, the article details the architecture of international trade regulation and the operational procedures of the Codex Alimentarius Commission (the Codex), the intergovernmental organisation in which international food standards are set. Thirdly, the role of scientific expertise to the standard setting process in the Codex is explored through a case‐study of the attempt to establish an international definition for dietary fibre. The article concludes by reflecting upon the importance of contestation over knowledge claims to the conduct of agri‐food governance.

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)0.017
metaresearch head score (Gemma)0.026
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: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.028
Scholarly communication0.0110.008
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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