Disciplinary Responsibilities of Judges in Common Law Legal Systems: A Comparative Study in the Contexts of USA, England, and Canada
Bibliographic record
Abstract
Disciplinary law, as a subcategory of public law, investigates the major regulations of the punishments for the employees of a highly creditable organization. Disciplinary law is different from criminal law and the purpose of punishment in these two types of law is not the same. In the criminal law, the purpose of punishment might be criminal deterrence, delinquent civilization and training, or victim cooling, whereas in disciplinary law, the major purpose of punishment is to monitor the maintenance and correct carrying of job responsibilities. Because of the position and authority of judges, their behavior would have important positive or negative effects on the lives and rights of litigators. Therefore, in the developed countries, the behavioral manuals and moral codes are set for the definition of disciplinary responsibilities of judges. In the same vein, the control of judge behavior law was legislated in 1390 in Iran. A comparative study of the different legal systems can contribute to the identification of weaknesses and strength points of the legislated law. Moreover, the investigation of position and disciplinary regulations of judges in those countries which have their legal system based on the Common Law can be a suitable criterion of measurement for identification of predicted shortcomings in the law and regulations of Iran with respect to the position and role of judges in these systems. For this purpose, the present study investigates the issue of judge’s disciplinary responsibilities in the contexts of United States of America, England, and Canada.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".