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Record W2915184409 · doi:10.4337/9781788977821.00020

Public policy considerations in intellectual property-related international investment arbitration

2020· book-chapter· en· W2915184409 on OpenAlexaboutno aff
Simon Klopschinski

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsTribunalArbitrationIntellectual propertyInvestment policyLegislationInvestment (military)Public policyForeign direct investmentInvestment arbitrationLawBusinessPolitical sciencePublic administrationLaw and economicsEconomicsInternational investment

Abstract

fetched live from OpenAlex

In the investment arbitration Philip Morris v. Uruguay the arbitral tribunal rejected Philip Morris’ claim that Uruguay’s anti-smoking legislation expropriated the tobacco company’s trademarks. In its reasoning, the tribunal largely deferred to Uruguay’s policy decision to curtail tobacco companies’ business operations for the purpose of enhancing public health. Philip Morris v. Uruguay raises the question of whether there are, apart from public health, other public policy considerations which the tribunal should have given more weight to, e.g. the promotion of foreign investment and the protection of intellectual property (IP). The chapter explores the concept of ‘public policy’ and how IP law, WTO law and international investment law, i.e. the legal regimes relevant to IP-related investment arbitration, deal with public policy considerations. The chapter also reviews the handling of public policy considerations in the IP-related investment arbitrations Philip Morris v. Uruguay and Eli Lilly v. Canada, as well as Bridgestone v. Panama.

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)0.004
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.007
Scholarly communication0.0140.009
Open science0.0010.002
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0100.002

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 head0.053
GPT teacher head0.228
Teacher spread0.175 · 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
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
Published2020
Admission routes1
Has abstractyes

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Same venueEdward Elgar Publishing eBooksSame topicInternational Arbitration and Investment LawFrench-language works237,207