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Record W2730095281 · doi:10.1111/twec.12515

How did investor‐state dispute settlement get a bad rap? Blame it on<scp>NAFTA</scp>, of course

2017· article· en· W2730095281 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Economy · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBlameTreatyState (computer science)International tradeInvestment (military)Foreign direct investmentCorporate governanceBilateral investment treatyInvestor-state dispute settlementEconomicsSettlement (finance)International economicsLaw and economicsLawPolitical scienceInternational investmentMacroeconomicsPoliticsFinanceComputer science

Abstract

fetched live from OpenAlex

Abstract In the short history of the US bilateral investment treaty ( BIT ) programme, there have been no instances of dispute settlement cases initiated against the United States by firms from BIT countries. The NAFTA experience changed that. Where other studies have only hinted at the reasons for NAFTA controversies, this paper makes clear three causal factors: (i) changing patterns and intensity of FDI , (ii) the application of those rules to developed countries amid those changing FDI patterns and (iii) ambiguities in ISDS rules themselves. The paper explores these and traces the ways in which lessons of the NAFTA have been instrumental in changing the pursuit of investment protection agreements. BIT s used to be uncontroversial, but the NAFTA focused attention on reforms to ISDS that maintain the utility of BIT s in the governance of FDI , without creating a legal structure for simply challenging the state.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.233
Teacher spread0.213 · 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