Bibliographic record
Abstract
Criminal justice institution undertakes the duty to investigate about legal cases and complaints, to issue the judgment and to enforce it on time through proper hearing and without any dely. Such actions can play an effective role in reducing the possibility of delinquency and victimization. As an essential element of procedure, victimization has not succeeded to recover its real right. Many criminologists have focused their researches on victims to solve the riddle of victimization and etiology of crimes. Criminologists also intended to assess victims’ roles and shares in the process of crime commission. In addition, they intend to amend criminal provisions based on a victim-based approach to protect the victims through establishing new criminal institutions. Because of this, criminal justice system will change due to the effects of revolutions of victimization considered as the central core. This has led to an increase in paying attention to the victim’s needs and rights in criminal system. The necessity of protecting the victim has not yet been recognized in Iranian statutes. This issue has not a place in criminology researches in Iran. However, we can observe the existing shortages in the area of protecting the victim and their status in Procedure Code through studying the victim’s role. The author of the present article has studied the necessity of establishing special institutions to fill the existing gaps considered by Iranian legislator in New Criminal Procedure Code 2013. The author has also dealt with the protection of victims based on literature review, library search and related sources.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".