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The Trouble with Foreign Investor Protection

2020· book· en· W3115724940 on OpenAlexaff
Gus Van Harten

Bibliographic record

Venuenot available
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsYork University
Fundersnot available
KeywordsBusinessInvestor protectionFinance

Abstract

fetched live from OpenAlex

Abstract Governments are rightly discussing reform of investment treaties, and of the powerful system of ‘investor–state dispute settlement’ (ISDS) upon which they rest. It is therefore important to be clear about the crux of the problem. ISDS treaties are flawed fundamentally because they firmly institute wealth-based inequality under international law. That is, they use cross-border ownership of assets, mostly by multinationals and billionaires, as the gateway to extraordinary protections, while denying equivalent safeguards to those who lack the wealth required to qualify as foreign investors. The treaties thus have the main effect of safeguarding an awe-inspiring set of rights and privileges for the ultra-wealthy at the expense of countries and their populations. This book shows how ISDS came to explode in a global context of extreme concentration of wealth and of widespread poverty. The history of early ISDS treaties is highlighted to show their ties to decolonization and, sometimes, extreme violence and authoritarianism. Focusing on early ISDS lawsuits and rulings reveals how a small group of lawyers and arbitrators worked to create the legal foundations for massive growth of ISDS since 2000. ISDS-based protections are examined in detail to demonstrate how they give exceptional advantages to the wealthy. Examples are offered of how the protections have been used to reconfigure state decision making and shift sovereign minds in favour of foreign investors. Finally, the ongoing efforts of governments to reform ISDS are surveyed, with a call to go further or, even better, to withdraw from the treaties.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.689
Threshold uncertainty score0.999

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.025
GPT teacher head0.192
Teacher spread0.167 · 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.

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

Citations28
Published2020
Admission routes1
Has abstractyes

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