Civil Liability in Construction Contracts and Compensation Practices in Iranian Law with an Emphasis on British Law
Bibliographic record
Abstract
The huge volume of construction activity in our country, is done in compliance with the Treaty and the general condition of Treaty. Although there is no legal requirement but even in private sector activities, these conditions are considered because total material of general conditions of Treaty is largely justifying the employer. Civil liability and contracts in construction contracts can help to a large extent. The subject of this study is to find an answer for the question which what is the basic difference between Iranian and British laws on compensation practices in construction contracts? And also what's the difference between compensation basic conditions in construction contracts in Iran and Britain law? In Iranian law, compensation practices in construction contracts is implementation of the same commitment in the first place and the compensation is in case that it is explicitly foreseen in the contract; while compensation is existed in the British legal system compensation practices in construction contracts; While compensation is existed in the British legal system compensation practices of construction contracts and there is not a concept as implementation of the same commitment as one of the compensation practices. Compensation may be stipulated in the contract in the Iran's law or customs or law requires compensation, in British law also, compensation does not require to be stipulated in the contract.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".