A Comparative Study of Judicial Control in Iran, U.S.A and Canada
Bibliographic record
Abstract
Supervision and control need tools and techniques that would usually take two forms: the first form is that the same court that hears claims and complaints submitted by the departments and its agents, handles other claims and all the claims are processed by these courts of justice. Another form of judicial supervision is supervision in a dual judicial system and that is a judicial system wherein only specialized courts are competent enough to review administrative claims and to investigate the conducts of the department and its agents. In this paper, we deal with how these tools are used in advanced legal systems like the U.S., and Canada and the Iranian legal system. The result we discover in the end is that in all stages of supervision by the supervisor and the supervised, there must be a sense of accountability to people and officials and this will be achieved by transparency in performance. In the absence of transparency supervision will be disrupted and some economic and administrative corruption will arise, because wherever there are secrecy and monopoly, the results will be inevitably corruption.
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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 | 0.000 |
| 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".