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Record W3092915538 · doi:10.33774/apsa-2020-fsht6

The Political Economy of Designing Bilateral Investment Treaties

2020· preprint· en· W3092915538 on OpenAlexaff
Jiayi Zhang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeopoliticsTreatyInvestment (military)PoliticsSettlement (finance)International economic lawBilateral investment treatyPolitical economyPolitical scienceInternational tradeEconomicsForeign direct investmentLawInternational investmentInternational lawPublic international lawFinance

Abstract

fetched live from OpenAlex

Why do some bilateral investment treaties provide a high level of dispute settlement protection to investors while others do not? It has been widely debated whether bilateral investment treaties are economic agreements or political tools. Both economic and political approaches have produced some solid evidence to shed light on the proliferation of bilateral investment treaties. Yet neither of them has provided a satisfactory answer. We believe bilateral investment treaties, as a form of international treaty by nature, should have both economic and geopolitical implications, and thus a good explanation needs to address both economic and geopolitical motivations. We argue that both economic and geopolitical considerations shape states’ preferences in designing dispute settlement provisions. Specifically, economic needs have positive effects while geopolitical needs have negative ones on the strength of dispute settlement provisions.

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)0.023
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.052
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.009
Scholarly communication0.0110.008
Open science0.0010.004
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0120.001

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 head0.039
GPT teacher head0.244
Teacher spread0.205 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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