Bibliographic record
Abstract
The legal action of Waqf has unique conditions in terms of nature and the elements and artifacts, and free will it is lower than other contracts; so change it is simply not possible and for it, that good tradition is not common recently.Design sukuk and Islamic securities, especially bonds of Waqf are taken into consideration as one of the solutions to expand and develop their endowment of Waqf.Given the emerging nature of the bonds, explores the concept of, conditions, nature and effects necessary to appear, in order to make greater use of the capacity of these bonds and reduce the legal problems around them.The present research is based on this need discussed the nature and consequences of these bonds and Tried to search the library resources and Analytical method, in addition to the introduction and explanation, for expansion and further provide them.The results obtained from the study include: Firstly, bonds of Waqf to the participation of investors is to do a welfare project with the difference that this participation has no beneficial aspects and individuals of the first regardless of their entitlement to benefit.So it seems we can consecrate no profit participation as the nature of the bonds of Waqf in Iran's law.Secondly, in terms of practical, designing the the bonds of Waqf based on "Istisna" can be an appropriate model.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.976 | 0.974 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".