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Record W2279204706 · doi:10.18480/jjre.16.1

Trade Effects of Ensuring Export Disciplines through Parallelism: The Case of Skim Milk

2014· article· en· W2279204706 on OpenAlexaboutno aff
Satoshi Hokazono, Koshi Maeda

Bibliographic record

VenueThe Japanese Journal of Rural Economics · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyInternational tradeNegotiationExport subsidyParallelism (grammar)Competition (biology)International economicsEuropean unionBusinessTrade barrierImperfect competitionEconomicsFree tradeComputer scienceMicroeconomicsPolitical scienceMarket economy

Abstract

fetched live from OpenAlex

The purpose of this paper is to quantitatively analyze the trade effects of ensuring export disciplines through parallelism. A spatial equilibrium model is developed that includes export subsidies, exporting state trading enterprises (exporting STEs), and imperfect competition. The model is applied to the international skim milk trade. The main results of the policy simulations are as follows. First, the skim milk trade has been distorted by European Union (EU) export subsidies and exporting STEs in New Zealand and Canada. Second, the distortion may be substantially corrected by ensuring export disciplines through parallelism. Third, the EU will continue to advocate parallelism in ongoing WTO agricultural negotiations with support from the United States and Japan, which receive the benefits from such successful negotiations.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.001
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 head0.030
GPT teacher head0.221
Teacher spread0.192 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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