MétaCan
Menu
Back to cohort
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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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