Codes of Conduct for the Judiciary in Civil Law Countries: The Dutch Example
Bibliographic record
Abstract
Is a code of conduct for the judiciary necessary for safeguarding the reliability of courts? In the civil law tradition codes of conduct are not widespread. Some international initiatives follow the example of countries like the United States and Canada in drafting codes of conduct. Can a code make a contribution to the professionalism of courts? Is it necessary to translate legal safeguards for fair trial into a code? On basis of the Dutch experience and the case law of the Court on Human Rights in Strasburg this article analyses the relation between legal fundaments of fair trial, such as independence and impartiality and the envisaged content of a code of conduct. For various reasons a code of conduct is useful. In a more individualistic society in which shared norms and values are less obvious, a code of conduct can provide such shared values for judges. Such a code can provide more transparency and can support discussions about the does and don'ts of judges.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".