The International Task Force On Mixed Mode Dispute Resolution: Exploring The Interplay Between Mediation, Evaluation And Arbitration In Commercial Cases
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.234 | 0.147 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.015 | 0.035 |
| Scholarly communication | 0.032 | 0.022 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".