Regulatoryism of Voluntary and Involuntary Withdrawal in the Attempt of Crime in the Light of American Law
Bibliographic record
Abstract
Measuring the will of the perpetrator at the time of withdrawing from committing a crime in proportion to whether it is voluntary or involuntary is one of the most important topics of attempt of crime since the main core of renunciation is the spiritual element, which cannot be easily understood. Therefore, it is necessary to make a fine distinction between voluntary and involuntary withdrawal by codification. Finally, in this article, by using the descriptive-analytical and library method, it was found that there are two types of withdrawal criteria for the existence of conditions beyond the perpetrator's will. The first category is human obstacles, which are either third parties or victims, and the second category is non-human obstacles, which are either indirect obstacles or direct obstacles related to crime. In the first type, withdrawal is involuntary, and in the second type, indirect obstacles are voluntary withdrawal, and in direct obstacles, involuntary withdrawal. The American Criminal Law has regulated voluntary withdrawal by adding the phrase "full intent to withdraw" and specifying conditions such as the presence of a third party, the severity of the crime or the victim's resistance, or changing the criminal purpose of voluntary withdrawal. In contrast, Iran's approach is only accepting the principle of withdrawal without stating the rules. Therefore, it seems that the American approach in expressing the rules is considered more efficient. However, the attention of the two criminal systems to the development of the circle of renunciation to prevent the crime or sometimes the irreparable damages of the total crime and to encourage the criminals to avoid committing the crime seems to be considered.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".