Theory of "Lost Opportunity" Theory in Iranian Law
Bibliographic record
Abstract
"Lost opportunity" theory by considering opportunities valuable as a chance, fortunes, and with the beliefs that opportunity is a material and spiritual right which has been violated by guilty. Therefore, it seeks for an approach to compensate the damage resulted from the loss of opportunity for gaining a profit or avoiding losses. This theory has been accepted for many years in European and American countries and in the courts, leads to issue many verdicts. However, either in Iranian law or jurists' and theologians opinions, there is no writing to confirm or deny this fact expressly. Also, about this theory sometimes there is no sputum and distinguishing between these two issues for its own complexities, as well as the parallel with the non-profit issue. Though contemplated on the basis of civil liability established in some laws such as Article VI of the civil liability law, for example, the rule of remuneration in sharecropping, it becomes clear that the legislator shows flexibility. Also, according to the conventional view and the context of some Jurists, the general rule has no harm, which considers the base of the civil liability as valuable.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".