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Record W3137634056

Geographical indications and generic names in international trade law: A conditio sine qua non?

2020· article· en· W3137634056 on OpenAlexaboutno aff
Gabriele Gagliani

Bibliographic record

VenueRevue internationale de droit economique · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsSine qua nonNegotiationPolitical scienceInternational tradeChinaIntellectual propertyInternational lawLawBusiness
DOInot available

Abstract

fetched live from OpenAlex

Geographical indications (GIs) have been at the center of international debates for a long time. Recently, several events have led to remarkable developments in the field. The EU has doubled down its efforts in promoting GI protection at the international level. Recent international agreements, such as the 2015 Geneva Act of the Lisbon Agreement on Appellations of Origin and Geographical Indications under the auspices of WIPO, or the bilateral trade agreements with Canada, China, and Japan, among others, have led the EU to claim important victories and progress on the international protection of GIs. Concurrently, the US has stepped up its efforts to put aside market sectors for generic names, i.e., names that are not protectable under GIs. The USMCA between the US, Canada, and Mexico, and the Economic and Trade Agreement between the US and China are good examples of the new US strategy. This article maps these recent developments and argues that GIs have recently taken up a whole new prominence in international trade law. This situation has been accompanied by a change in the stances of the EU and the US. Indeed, the EU appears to have adopted an increasingly rigid stance on GI protection, which has become a conditio sine qua non for multilateral and bilateral negotiations. In turn, and in response to this change, generic names have figured more prominently in the US international trade agenda. This notwithstanding, the gap between the positions of the EU and the US is not unbridgeable since, in reality, both parties legally recognize both GIs and generic names.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.711

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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 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
Published2020
Admission routes1
Has abstractyes

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