Procedural Cross-Fertilization in International Commercial and Investment Arbitration: A Functional Approach
Bibliographic record
Abstract
Abstract This article examines the potential for beneficial procedural cross-fertilization between internationalcommercial and investment arbitration from a functional perspective. The article argues that botharbitration regimes share a ‘private’ dispute resolution function of resolving specific disputes, butonly investment arbitral tribunals also exercise a ‘public’ law-making function of developing the lawapplicable to the resolution of disputes. The article considers two recent procedural developmentsin international arbitration rulesjoinder of third parties and publication of arbitral awardsin thelight of these private and public functions. It argues that joinder, as an efficiency-enhancingmeasure, can lead to beneficial cross-fertilization between commercial and investment arbitrationbecause it reinforces the ‘private’ dispute resolution function shared by both regimes. In contrast,the default publication of arbitral awards, to the extent that it is intended to be systematic and createinformal precedent, is appropriate in investment but not in commercial arbitration because onlyinvestment arbitral tribunals exercise a ‘public’ law-making function that justifies and stands tobenefit from this practice. In this regard, the article rejects three rationales for default publication ofinternational commercial arbitral awards: improving consistency/predictability, enhancingtransparency and developing transnational commercial law. The article concludes that crossfertilizationbetween investment and commercial arbitration can be valuable so long as it concernstheir shared private dispute resolution function. However, attempting to develop internationalcommercial arbitral practice in the shadow of the public law-making function of investment arbitraltribunals may result in counterproductive practices and undermine the proper functioning ofinternational commercial arbitration as a whole.
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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 | 0.046 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".