Arbitrator Behaviour in Asymmetrical Adjudication: An Empirical Study of Investment Treaty Arbitration
Why this work is in the frame
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Bibliographic record
Abstract
The study examines arbitrator behaviour in the uniquely context of investment treaty arbitration. It employs the method of content analysis to test hypotheses of systemic bias in the resolution of jurisdictional issues in investment treaty law. Unlike earlier studies, the study examines trends in legal interpretation instead of case outcomes and finds statistically significant evidence that arbitrators favour (1) the position of claimants over respondent states and (2) the position of claimants from major Western capital-exporting states over claimants from other states. There is a range of possible explanations for the results and further inferences are required to connect the observed trends to rationales for systemic bias. The key finding is that the observed trends exist and that they are unlikely to be explained by chance. This gives tentative empirical evidence of cause for concern about the use of arbitration in this context.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it