From Principles to Rules: The Case for Statutory Rules Governing Aspects of Judicial Disqualification
Bibliographic record
Abstract
The common law “reasonable apprehension of bias” test for judicial disqualification is highly fact- and context-specific. While there are good reasons for this approach as a general proposition, it also gives rise to considerable uncertainty for both judges and litigants in considering whether or not it is appropriate for a judge to sit in a marginal case. This article explores statutory judicial disqualification regimes in the United States, Germany, and Quebec to gain insights into how statutory rules can be employed to provide greater clarity to judges and litigants who are addressing situations that have the potential to give rise to judicial disqualification. Using these insights, the authors then propose the use of statutory rules to address problem areas with respect to professional relationships with former colleagues and clients, prior judicial involvement with litigants, extrajudicial writings, and procedures for making determinations concerning judicial disqualification.
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 | 0.119 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.090 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.022 | 0.031 |
| Insufficient payload (model declined to judge) | 0.003 | 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".