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Record W3008673990 · doi:10.12985/ksaa.2019.27.4.083

An Analysis of WTO Disputes in Aircraft Manufacturing Industry

2019· article· en· W3008673990 on OpenAlexaboutno aff
Hae Jun Lee, Sun Ihee Kim

Bibliographic record

VenueJournal of the Korean Society for Aviation and Aeronautics · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)BusinessInternational tradeAircraft industryManufacturingMember statesEuropean unionEngineeringAeronauticsMarketingFinance

Abstract

fetched live from OpenAlex

In order to promote the domestic aircraft manufacturing industry, this study analyzed the limitations of the preceding study on the WTO dispute concerning civil aircraft by summarizing the latest developments and issues in the mid-range aircraft dispute between Brazil and Canada and the large civil aircraft dispute between the United States and the EU. Based on the results of the study, we should look closely at WTO regulations and existing cases of disputes to find maximum support measures, and we believe that in order to stimulate the domestic aircraft manufacturing industry, we should refrain from publicly specifying support measures in the data, such as laws and policies, utilize the WTO SCM Agreement exceptions, and strengthen links with international cooperation and other industries.

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)0.011
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0100.013
Science and technology studies0.0050.003
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.002
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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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