Institutionalization of the Restorative Justice Principles in Conflict Resolution Council
Bibliographic record
Abstract
Recently, the restorative justice has been considered as a novel method in the legal and criminal system. Attending the restorative justice is directly related to victims’ rights and interests that is often considered as a supplementary way. However, in various legal systems, special attention has been paid to restorative justice and its principles has been recognized in many legal systems, including common law legal system. In Iran, attention and emphasize on the subject of restorative justice do not have a long history. However, currently, in some of the Iranian judicial and legal entities, these principles have been approved. The important subject is to what extent has these principles been institutionalized and approved in these two legal systems. In this paper, an attempt has been made to investigate the position and acceptance and institutionalization amount of the principles of the restorative justice in the conflict resolution council in Iran and similar entities in common law regulations. The findings obtained from the investigations conducted in this context illustrate that in conflict resolution council and their structures, attending the restorative justice has been highlighted. In the theoretical context, too, the principles of restorative justice are adapted to conflict resolution council objectives and tasks.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".