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Record W3099377421 · doi:10.1093/aepp/ppx048

Impact of European Union–U.S. Organic Equivalency Arrangement on U.S. Exports

2017· article· en· W3099377421 on OpenAlexaboutno aff
Iryna Demko, Edward C. Jaenicke

Bibliographic record

VenueApplied Economic Perspectives and Policy · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
FundersEuropean CommissionPennsylvania State UniversityU.S. Department of Agriculture
KeywordsEuropean unionQuarter (Canadian coin)International tradeOrganic farmingInternational economicsAgricultural economicsAgricultureWorld tradeEconomicsBusinessGeography

Abstract

fetched live from OpenAlex

Abstract This study uses the synthetic control method to investigate the impact of the 2012 bilateral organic equivalency arrangement between the European Union and the United States, the two largest organic markets in the world. Employing the newly‐available USDA Global Agricultural Trade System (GATS) data on organic trade, we collectively analyze 23 products of U.S. organic exports representing fresh produce, coffee, and tomato sauce, at the quarterly level during the 2011–2014 period. We find that the policy generates an increase of 9.1% in the organic exports of these products to the European Union each quarter.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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