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Record W2351771092

International Claims:State Practices Based on Lump Sum Agreements

2012· article· en· W2351771092 on OpenAlexvenueno aff
Mou Wen-f

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffRespondentBusinessState (computer science)Settlement (finance)ChinaTreatyWaiverLawLaw and economicsPaymentPolitical scienceEconomicsFinance
DOInot available

Abstract

fetched live from OpenAlex

Lump sum agreements have been widely and frequently employed in the practice of international claims arising out of expropriation and nationalization on a large scale of property of aliens.The common provisions lie in this type of claims agreement providing payment by respondent state of a fixed sum of compensation to claimant state,eligibility of claimants,compensable claims,sole responsibility on the claimant state to distribute the compensation funds,waiver by claimant state to bring any further claim against respondent state,etc.Afterwards,the state authority of the claimant state will be in charge of adjudicating claims brought by its nationals.Addressed here are some legal aspects of the above-mentioned state practices,including claims by and against China both as claimant state and respondent state respectively.With the increasing scale of direct investment in and from China,such dispute settlement method might be of help in protecting China's national interests,including overseas interests.

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)0.012
metaresearch head score (Gemma)0.023
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 score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0050.011
Scholarly communication0.0110.008
Open science0.0020.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0070.002

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 head0.109
GPT teacher head0.385
Teacher spread0.276 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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