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Record W2767915429 · doi:10.54648/joia2017040

<i>Eli Lilly v. Canada</i>: A Patently Clear-Cut Dismissal on the Facts, but Opening the Door for Future Claimants on the Law

2017· article· en· W2767915429 on OpenAlexaboutno aff
E.M. Leikin, Boris Kasolowsky

Bibliographic record

VenueJournal of International Arbitration · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsnot available
Fundersnot available
KeywordsTribunalLawPlaintiffArbitrationSettlorPolitical scienceExpropriationWaiverEconomic JusticeIntellectual propertyHigh CourtLaw and economicsBusinessEconomics

Abstract

fetched live from OpenAlex

In March 2017, the Tribunal in Eli Lilly v. Canada issued a unanimous final Award, dismissing all claims on the basis that the claimant ‘failed to establish the factual premise of its case’. Despite finding against Eli Lilly on the facts, the Lilly decision appears to have opened the door (at least slightly) for investors on two novel points of law. First, the Tribunal suggested that a judicial decision which does not constitute a denial of justice may nonetheless qualify as a breach of the North American Free Trade Agreement's (NAFTA's) minimum standard of treatment (Article 1105) and/or protection against expropriation (Article 1110). Second, the Tribunal did not reject – and indeed appeared willing to consider – the proposition that an investor may support its investment arbitration claims by relying on a host state’s international commitments on the treatment of intellectual property rights. Given the potential importance of these issues in future arbitrations, this article first provides an overview of the Lilly decision. It then explores in greater depth the two legal issues raised above, examining the arguments put forward by the parties, the view expressed by the Tribunal and the potential effect on the development of international investment law, with a particular focus on how these issues may come into play in any future claims arising from the issuance of a compulsory license.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.033
GPT teacher head0.302
Teacher spread0.269 · 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.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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