Legal System Governing on Water Pollution in Iran
Bibliographic record
Abstract
In the present era, water contamination represents one of the considerable environmental problems. Population growth along with ever increasing industrial developments has resulted in the contamination of most of the water resources in the world, bringing about serious problems for humans and other living organisms. According to the human life on earth depends on the way different water resources are exploited, the most important way to preserve the quality of water resources is to codify appropriate regulations and standards and develop plans for proper and principled implementation of them. Therefore, it seems to be necessary to take required actions to manage water resources optimally. In this regard, one of the most significant legal tools is the law. Following a descriptive-analytic approach, the present research aims to consider legal challenges in the context of water contamination briefly. Investigations indicate that, given the limitations in water resources, in future, water contamination will raise serious problems for the country should the solutions and measures required for tackling this issue are not well incorporated into respective regulations. As such, in order to systemize the activities within this scope, it is necessary to codify a comprehensive act about different water-related topics, so as to cover all separate and sparse pieces of regulations on water. Further, acquiring help from experts when preparing the regulations with an emphasis on the inhibitory role of penalties, roles of NGOs and culture-making in the society will contribute to the successful legal protection of the quality of water resources.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".