MétaCan
Menu
Back to cohort
Record W4386508110 · doi:10.54097/hbem.v16i.10602

Impact of International Investment Dispute Arbitration on the Protection of Intellectual Property Rights in Host States: Current Status and Development Trends

2023· article· en· W4386508110 on OpenAlexaboutno aff
Xiaorui Chen

Bibliographic record

VenueHighlights in Business Economics and Management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual propertyArbitrationInvestment (military)Investment protectionBusinessTreatyInvestor-state dispute settlementInternational tradeForeign direct investmentAutonomyExpropriationState (computer science)International lawInternational investmentLaw and economicsLawEconomicsPolitical sciencePolitics

Abstract

fetched live from OpenAlex

In recent years, international investment treaties have included intellectual property rights into the category of "investment", and the protection methods are no longer limited to disputes between states (diplomatic protection and WTO dispute settlement). Investors can start international investment arbitration proceedings against host states through investment treatment clauses and Investor-state dispute settlement. Cases such as the Morris Asia v Australia and Eli Lilly v. Canada show that intellectual property owners are trying to use international investment treaties and their arbitration mechanisms more actively to challenge IP policies (measures) in host states. However, this situation will affect the IP policy and practice of the host state and break the balance established between the protection of private rights and the welfare of society. Based on this, host states should be more careful in establishing international treaties that specify IP policies and the obligations of investors. At the same time, host states and the international community have made clear the boundaries of IPR protection in investment treaties, and it is necessary to maintain the autonomy of host states' IPR policies (measures).

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)0.010
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.005
Scholarly communication0.0090.008
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.029
GPT teacher head0.237
Teacher spread0.208 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHighlights in Business Economics and ManagementSame topicInternational Arbitration and Investment LawFrench-language works237,207