A Comparative Study of Absolute Liability Offense in Iran and the UK
Bibliographic record
Abstract
One characteristic of the force of law in the country, the integrity of the rules in all areas of all aspects of creation into account the distinction between crime and the crime and failed or incomplete in acts of crime and crime as the withdrawal. In this respect the rules on penalties culpability in the crime has been proposed that the content of the crime with absolute responsibility of these categories has manifested. Under the Articles 144 and 145 of the Latest version Islamic criminal law (2013), Create unintentional offenses, subject to verification of the fault committed. In crimes ranging from quasi-intentional unintentional deviation as retaliation book rules apply. Legislator to commit a fault, the reason for the error is considered criminal, which has always been considered an objective measure and a ruler (in Article 145), while the common law under subsection (1) "criminal law to crimes" adopted 1981 crime start as the offense is punishable total. This study showed that certain similarities between the laws. In this context, the two internal laws and the common law can be found, in which the underlying offense of absolute liability is not fixed in the courts. Always treat judges and lawyers in the face of legal texts are not consistent because of the lack of transparency and clarity of the rules. In particular, in the common law, when a crime for the first time in cour t, and a warrant has been issued about it in terms of predicting the law and with regard to the interpretation of judges, procedural difference is more tangible.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".