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Record W4224997288 · doi:10.1002/aepp.13278

Governing food safety through meso‐institutions: A cross‐country analysis of the dairy sector

2022· article· en· W4224997288 on OpenAlexaffabout
Claude Ménard, Gaetano Martino, Gustavo Magalhães de Oliveira, Annie Royer, Maria Sylvia Macchione Saes, Paula Sarita Bigio Schnaider

Bibliographic record

VenueApplied Economic Perspectives and Policy · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsUniversité Laval
FundersCollege of Natural Resources and Sciences, Humboldt State UniversityUniversidade de São PauloFundação Getulio Vargas
KeywordsArgument (complex analysis)Bridging (networking)Institutional analysisMacroBusinessFood safetyNew institutional economicsIndustrial organizationEconomicsMicroeconomicsComputer scienceComputer security

Abstract

fetched live from OpenAlex

Abstract This article builds on new institutional economics to characterize the functions played by meso‐institutions in bridging the gap between the macro‐institutional layer at which general rules are established and the micro‐institutional layer within which transactions are organized. The argument is substantiated through a comparative analysis of the regulatory settings designed to secure the safety of raw milk in Brazil, Canada, and Italy. We show that similar rules may lead to very different operational impact, depending on the arrangements through which these rules are implemented. The analysis also points out some consequences for the organization of supply chains and public policies.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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 designObservational
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

Citations22
Published2022
Admission routes2
Has abstractyes

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