MétaCan
Menu
Back to cohort
Record W3177426490

A Hard Pill to Swallow: A Critical Look at Eli Lilly & Co.'s NAFTA Challenge of the Canadian Patent Regime, and Its Potential Side Effects

2013· article· en· W3177426490 on OpenAlexaboutno aff
Damian Hakert

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsNoticeCONTESTArbitrationLawBusinessPolitical scienceDoctrineGovernment (linguistics)Patent lawLaw and economicsIntellectual propertyEconomics
DOInot available

Abstract

fetched live from OpenAlex

On September 12, 2013, Eli Lilly & Co., in filing its Notice of Arbitration with the North American Free Trade Agreement against the Government of Canada, became the first private investor to contest a national patent regime through arbitral means. In the Notice, Lilly alleges that Canada violated NAFTA Articles 1110 (covering expropriation) and 1105 (covering mini- mum standards of treatment) by allowing Canada Federal Courts to unlawfully invalidate two of Lilly’s patents, CA 2,041,113 and CA 2,209,735, protecting the compounds comprising Zyprexa and Strattera, respectively, through application of its controversial “promise doctrine.” Whether arbitration through NAFTA is an appropriate way to contest a NAFTA member state’s patent regime is hotly contested. But Canada Federal Courts have invalidated an increasing number of pharmaceutical patents for failing to meet the promise doctrine, leaving pharmaceutical companies in Canada uncertain as to the extent of their patent rights. Still, NAFTA allowing pharmaceuti- cal companies to successfully dispute national patent laws could have significant future consequences. This note outlines the circumstances surrounding Lilly’s dispute, analyzes the dispute’s viability, and explores various potential implications of the dispute going forward.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.038
GPT teacher head0.211
Teacher spread0.173 · 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
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicIntellectual Property and PatentsFrench-language works237,207