Examining the Criminological Foundations of Intentional Crimes in the Criminal Law of Iran and Canada
Bibliographic record
Abstract
Intentional crimes occur in two forms: intentional crimes against life, which result in the death of the victim, and intentional crimes below the threshold of life, which cause harm to a body part of the victim. The occurrence of crimes in societies fundamentally depends on the presence of underlying factors that facilitate criminal behavior. Therefore, the judicial system must identify the root causes of crime and take appropriate measures to address them. One of the significant causes of criminal behavior is the mental health issues of the perpetrator. Under Iranian law, an intentional crime is an offense committed by an adult, sane, and voluntary individual. The legislator has explicitly defined the concept of intent in the relevant provisions (Articles 289 and beyond) of the Islamic Penal Code, enacted in 2013, to determine the classification of intentional crimes. In Canadian law, under Section 229(a)(ii) of the Criminal Code, an intentional crime is defined as the deliberate intent to harm another person, with the perpetrator being aware that such actions are likely to result in death and displaying reckless disregard as to whether their actions lead to the killing of another human being. In intentional crimes against physical integrity, where direct harm is inflicted on individuals, the criminal lawsuit holds a private nature. In Iranian law, the primary punishment for intentional crimes is retribution (Qisas), whereas in Canada, which follows the common law system, life imprisonment is considered the principal punishment for such offenses. The research method employed in this article is descriptive and analytical. This study seeks to answer the question: What are the criminological foundations of intentional crimes in the criminal law of Iran and Canada? The objective of this research is to determine the criminological foundations of intentional crimes in the criminal law systems of Iran and Canada.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".