Sentencing Postponed in the Penal Code in 1392
Bibliographic record
Abstract
Sentencing postponed is one of the new installations of IPC (The Islamic Penal Code) that its Basics of criminology have not been studied yet. Hence, human approach to punishment and reduce resort to punishments can cause decrease in crime and commits compatibility. Postponing the Sentence towards criminals in order to decriminalize and not resort to punishment is one of the institutions that can achieve to the Goals considered by Criminal Matters policymakers In order to reduce recidivism. Therefore Iranian legislator well as in order achieving the objectives of long-standing human means reducing crime rates, is trying to impose new facility with Reform-driven approach. Postponement of the sentence is one of the Facilities that in The Penal Code adopted 1392attracted the attention of Legislator postponing institution by delaying the sentence gives the opportunity to the offender to return to society, And once again resume a healthy social life. Postponing sentence is leniency that only is includes limited offenses with prescribed punishment. Crimes that because of their non-violent and light of them and less dangerous of their commits Faster and easier leads to reduce recidivism and offender rehabilitation. this study holds that by Documents library method (analytical descriptive), paid to the new installations Islamic Penal Code related to the postponed sentence of offenders and crimes and offenses that would be subject to such a ruling. It should be noted that the statistical community of this study is all books, articles, laws and reputable sites that researchers in the current study uses them.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".