Money Laundering in Iran’s Law and International Document
Bibliographic record
Abstract
Money laundering or money laundering is a set of operations which transform the illegitimate and illegal property to legitimate and legal property and This phenomenon is one of transnational organized crime that has detrimental effect and impacts on the local and international level in the fields of social, political, economic and security and for this reason, many international conventions including the Vienna and the Palermo Convention have stressed to criminalize and combat it and in domestic law to combat money laundering as a crime have been considered by the law. In Jurisprudence (figh) there are verses, traditions and legal rules, which demonstrate criminalization of this phenomenon; this paper, in detail discussed this Jurisprudence reasons; as well as relationship of money laundering with Khums(one-fifth) of lawful property mixed with forbidden money and conflict of Criminalization of money laundering with some important Islamic legal principles such as The presumption of ownership and Possession of owner to his property have been pointed and investigated. So this study, analyzed the Jurisprudence foundations of the money laundering case and the prohibition of it has been concluded.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".