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Record W2500670030 · doi:10.1057/9781137515209_5

The World Trade Organization and Preferential Trade Agreements: The Case of Cultural Goods and Services

2015· book-chapter· en· W2500670030 on OpenAlexaboutno aff
Gilbert Gagné

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsStalemateInternational tradeLiberalizationFree tradeInternational economicsGoods and servicesTrade in servicesInternational trade lawEuropean unionPolitical scienceSalientProduct (mathematics)EconomicsEconomyLawPolitics

Abstract

fetched live from OpenAlex

Two contrasting perspectives on the treatment of cultural goods and services in international trade law have proved ever more salient since the early 1990s and in light of the digital revolution. For countries such as the United States, cultural goods and services should be considered like any other product, whereas for others, Canada and France in particular, they should be subject to an exception to the principles and rules of economic liberalization. Between these extreme positions, most countries seem favorable to a more or less pronounced form of cultural exception. In view of the difficulties in expanding liberalization commitments on cultural products at the multilateral level and the stalemate in the Doha Round, the main actors in the trade and culture debate, that is, Canada, the European Union (EU), and the United States, have each concluded their own preferential trade agreements (PTAs) with many countries throughout the world.KeywordsEuropean UnionWorld Trade OrganizationNorth American Free Trade AgreementCultural GoodCultural IndustryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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 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: Other · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.270
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2015
Admission routes1
Has abstractyes

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