Bibliographic record
Abstract
One way to resolve disputes and claims is to refer them to authorities rather than the courts of law.Among these cases, we can refer to arbitration.Although the settlement of disputes by arbitration is one of the effective ways to deal with claims, there are a series of particular disputes and claims that cannot be referred to arbitration or their referral to arbitration might encounter some restrictions.In fact, arbitrability indicates some bans and restrictions that every legal system takes into account to protect special interests.Iranian legislators explicitly prohibit the referral of a series of disputes to arbitration and these cases are not limitative because there are other claims that cannot be referred to arbitration due to their relationship with the general rules and the imperative laws as their proceedings by private judges is against public policy.There are some formalities for a number of claims and a case in point is Article 139 of Iranian Constitution and Article 457 of Civil Procedure which is concerned with the claims about public or state properties.Such claims can be referred to arbitration but there are terms and conditions for this referral such as the approval of the Committee of Ministers and the awareness or the approval of the Parliament.Therefore, in this study, an effort is made to investigate the concept of arbitrability and its variants in Iranian law.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.967 | 0.959 |
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".