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Record W2592410394

The International Task Force On Mixed Mode Dispute Resolution: Exploring The Interplay Between Mediation, Evaluation And Arbitration In Commercial Cases

2017· article· en· W2592410394 on OpenAlexaff
Thomas J. Stipanowich, Véronique Fraser

Bibliographic record

VenueFordham international law journal · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsArbitrationMediationDispute resolutionAlternative dispute resolutionConciliationDispute mechanismParty-directed mediationPolitical scienceSettlement (finance)Conflict resolutionPublic relationsBusinessLaw
DOInot available

Abstract

fetched live from OpenAlex

As mediation and other settlement-oriented intervention strategies have come into broader use in commercial dispute resolution, different views have emerged regarding the nature and purpose of some of these processes as a result of both individual choice and cultural or systemic factors. The potential for divergent perspectives or practices is enhanced when dispute resolution processes are mixed or matched. Mixed approaches involving the interplay between arbitration, evaluation and mediation are an increasingly important feature of the landscape of national and international commercial dispute resolution. This white paper was developed in connection with the convening of an international task force to explore the spectrum of national and international practices and perspectives associated with several mixed mode dispute resolution scenarios, including (1) mediators using nonbinding evaluation or mediator proposals as a means of encouraging settlement; (2) mediators setting the for arbitration by facilitating process discussions; (3) switching hats: mediators shifting to the role of arbitrator in the course of helping resolve a dispute (med-arb), or arbitrators shifting to the role of mediator; (4) arbitrators using various other approaches to set the stage for settlement; (5) arbitrators rendering consent awards based on a negotiated settlement; and (6) other kinds of interaction between evaluation, mediation, and arbitration.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0030.004
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.319
Teacher spread0.265 · 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 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

Citations24
Published2017
Admission routes1
Has abstractyes

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