Transnationalization of Domestic Law in International Commercial Arbitration Through Comparative Analysis: Challenges for Legal Profession
Bibliographic record
Abstract
The paper explores crucial role of comparative method in the interpretative practice of international commercial arbitration and examines in what ways, to what extent, in what context and to what effect it is being used in this field. It aims at highlighting how the “reformulated” practice of comparative analysis in arbitration differs from one developed by the domestic courts, and seeks to explain reasons, as well as consequences of this phenomenon. The comparative method is also perceived as a lens, focusing a number of key issues in arbitration, including its specific functional and legal setting, impact on legal profession and the dynamics of regional developments in this field. The discussion of the role of comparative approach in arbitration focuses on substantive law considerations, but it also refers to the issue of reconciling competing procedural standards in cross-cultural cases. The main goal of the paper is thus to unveil particularities of comparative method in arbitration, to explain its unprecedented popularity in this field and to demonstrate how it is being used as an instrument for what has been characterized as the arbitrators’ “inclination to ‘transnationalise’ the rules they apply”.
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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 | 0.034 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".