International Judges and Experts’ Impartiality and the Problem of Past Declarations
Bibliographic record
Abstract
The impartiality of international judges, fact-finders and rapporteurs is a central issue for the international rule of law. Although much attention has been devoted to conflicts of interest and prior office, the status of previous declarations that might impinge on impartiality remains a complex matter whose practical and theoretical ramifications have not been wholly addressed. This article explores the conditions under which prior utterances might impugn the impartiality of international judicial or other international mandate holders involved in the administration of international law. It proposes to frame the problem not merely as it relates to a particular kind of international agent (judge, or expert, or rapporteur), but more broadly as involving an assessment of the notion of impartiality as such. The article begins by proposing a broad outline of the international impartiality regime, drawing on recent cases and practice. It then makes the argument that impartiality should be evaluated by examining a broad range of factors that may demonstrate the presence of bias, and that are not reducible to a simple legal formula. The article seeks to make a contribution to outlining these factors on the basis of existing case law and best practices.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".