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Record W4251246921 · doi:10.54648/joia2019037

The New NAFTA: Scaled-Back Arbitration in the USMCA

2019· article· en· W4251246921 on OpenAlexaboutno aff
Daniel Garcia-Barragan, Alexandra Mitretodis, Andrew Tuck

Bibliographic record

VenueJournal of International Arbitration · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsArbitrationFree trade agreementInvestor-state dispute settlementPolitical scienceState (computer science)International tradeSettlement (finance)Investment (military)International investmentBusinessLawForeign direct investmentFree tradeFinance

Abstract

fetched live from OpenAlex

In December 2018, the United States, Mexico, and Canada entered into the United States- Mexico-Canada Agreement (USMCA), a new multilateral investment agreement to replace the 1994 North America Free Trade Agreement (NAFTA). This article summarizes the differences between the investor-state dispute settlement (ISDS) provisions provided in Chapter 11 of NAFTA and those covered in Chapter 14 of the USMCA from the perspective of the United States, Mexico and Canada. This article covers when an investor can assert claims under the USMCA (including NAFTA claims for legacy investments), what kind of claims can be brought, and what rules govern in USMCA arbitrations. The authors of this article conclude that the USMCA provides diluted ISDS provisions compared to NAFTA’s Chapter 11.

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)0.009
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: none
Teacher disagreement score0.402
Threshold uncertainty score0.800

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0100.003
Open science0.0010.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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
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

Citations2
Published2019
Admission routes1
Has abstractyes

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