Analytical Review of Body Damage Compensation Fund in Article 10 Third Party Insurance
Bibliographic record
Abstract
Body Damage Compensation Fund subject to Article ten of Law for Responsibility of Owners of Motor Vehicles is relatively a new legislative installation in Iran; it has been effective since 1968 in relation to victims under Article ten of the Law. Up to 2008, the Fund had not a significant role in due to lack of sufficient resources the subjects’ compensation. With the replacement of Amendment to Law on Third Party Insurance in 2008, the legislators have increased the amount of commitments in addition to paying a particular attention to Fund’s sources of income under Article 4 of this law. It resulted in gradual increase in the effective role of the Fund among other installations such as Public Treasury Fund. Despite the passage of about 40 years from the installations of this fund in Iran, the legal community, particularly judges and lawyers and legal experts are still unfamiliar with nature, role, and tasks of the Fund. The legal nature of the fund has not been discussed yet and its position has not been compared to other resources. Due to poor structure, insufficient financial resources, limited obligations, and lack of covering all damaged persons, the compensation fund had not been effectiveness until 2008. Its explanation is not only useful for juridical system and important for issuance of sentences but also it is helpful in the recognition of the obligations. In addition to taking into account the definition of the fund, this article ties to compare the Iranian version to one of the most developed systems in the world, New Zealand. It will show that the fund is responsible for the damages and it is regarded as a complementary means for compensating the damages having been imposed on innocent victims while its place is clear among other institutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".