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Record W3081726560 · doi:10.5539/jpl.v13n3p280

New Trends in Developing Alternative Ways to Resolve Financial Disputes

2020· article· en· W3081726560 on OpenAlexvenueno aff
Frolova Evgenia Evgenevna

Bibliographic record

VenueJournal of Politics and Law · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsArbitrationDispute resolutionAlternative dispute resolutionMediationJurisdictionOnline dispute resolutionDispute mechanismDispute boardPolitical scienceLaw and economicsLawConventionBusinessEconomics

Abstract

fetched live from OpenAlex

The authors investigate an issue of the appearance of new trends in developing alternative ways to resolve financial disputes. It has been found that: 1) selection of an arbitration forum for dispute resolution in the field of international finance instead of national courts of London and New York became an obvious reality that should be taken into account by politicians and entrepreneurs; 2) advantages and disadvantages of arbitration resolution of financial disputes are also obvious, so special attention should be paid to the new forms of dispute resolution clauses – hybrid dispute resolution clauses that authorize counterparties to select between the national judicial proceeding and the international arbitration, allowing the parties to select the most appropriate proceeding jurisdiction as following from the specific dispute based on advantages of both forums; 3) in connection with the popularization of alternative ways of dispute resolution in the field of financial relations it is prospective to use mediation for dispute resolution: the entry of Singapore Convention on Mediation 2019 into legal force and joining of global financial leading states to it can contribute to this; 4) in connection with the specifics of cross-boundary financial relations, and for dispute resolution, standard arbitration regulations are not always applicable, so now arbitration institutions tend to follow the way of including separate regulations with regard f the specifics of these disputes; the latest trend can be considered the creation of separate centres in the field of financial dispute resolution.

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)0.048
metaresearch head score (Gemma)0.039
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 score0.048
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.006
Science and technology studies0.0040.016
Scholarly communication0.0240.034
Open science0.0060.010
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0140.003

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 head0.036
GPT teacher head0.261
Teacher spread0.225 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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