Review and Application of Rule of No Loss and Negation of Distress and Constriction in Iranian Civil Law
Bibliographic record
Abstract
Jurisprudential rules are rules that are legislated on the way to gain divine religious commandments, but this use was not in a chapter of inference and mediation, but also it is in chapter of implementation and jurisprudential rules have been used as foundations of many articles legal in Iranian civil law. So considering the importance of these rules, the general aim of this research is investigate frequently used jurisprudential rules in Iranian civil law with an emphasis on (rule of no loss, negation of distress and constriction and beneficence). It should be noted, the rule of no loss, in addition to this that it can limit the circle of preliminary evidences as a secondary reason in personal loss cases, and it suggests overall policy in canonization the initial commandments, so no loss rule has not been used as a documentary, civil liability of compensation for losses. This matter correctly proves that "no loss rule" is as an expression of negation the loss verdict in Islam, not compensation for the losses. Distress and constriction is a general rule that Jurisprudents have referred to it in many cases, and thereby, they have passed a sentence to the negation of tasks which are required the distress and constriction for oblige.In the chapter of beneficence should also be noted that it includes the disposal of losses and also attracting the interest as well as because the provisions of beneficence rule are rational rules and rational affairs cannot be allocated. So much more certain of the beneficent rule in the legal relationships is where that person was trying to make benefit for others or wants to do the disposal of losses of him/her not to make benefit him/herself. The application of the rule of no loss and negation of distress and constriction is investigated in Iranian civil law in this article.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".