Bibliographic record
Abstract
This article considers the role of arbitrators in adjudicating the merits of international commercial disputes. It focuses, as a case study within this broader topic, on the interpretation of contracts. Interpreting contracts is a highly practical activity, but arbitrators’ approach to interpretation has important implications both for theory and for the success of arbitration as a means for the resolution of international commercial disputes. Are arbitrators more like judges, bound to apply the governing law according to strictly-defined rules, or more like commercially-minded problem-solvers? What approach best serves the needs of commercial parties?The article challenges a widespread attitude that arbitrators should interpret contracts according to their commercially reasonable meaning, regardless of the interpretative rules provided in the governing law. First, it documents this attitude in the published awards and in the ‘extra-judicial’ pronouncements of arbitrators. Second, it confronts the various arguments that might be made in favour of arbitrators departing from the governing law. Finally, it sets out a suggested approach for determining the appropriate interpretive method in any given case.
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 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 | 0.057 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.070 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".