Policy-Making of the Persian Gulf States Based on the Sustainable Development Goals in 2030 Agenda
Bibliographic record
Abstract
The closure of the Persian Gulf environment and the passage of tankers and the overuse of this region beyond international standards, have endangered the environmental status of this gulf. The dissemination of maritime culture, water economy and the inclusion of its policies in the laws of the eight countries of the Persian Gulf is essential to achieve sustainable development, given its various dimensions and practices. The main question is how effective the performance of Persian Gulf states can be in sustainably developing the marine environment of the Persian Gulf with emphasis on economic, social and environmental indicators of sustainable development? This article has analyzed the performance of the Persian Gulf countries in relation to the sustainable development of the marine environment, in an analytical manner and as a library research and, thus, laws should be applied in the Persian Gulf region as a general obligation of governments to protect the marine environment, in the form of a system of regional cooperation. Consequently, it can be expressed that achieving sustainable development in the marine environment of the Persian Gulf, can only be made possible via all of the eight countries playing the optimal role in interaction with each other and the strict implementation of international agreements on marine pollution prevention. The application of the 17 SDGs and the indicators mentioned in the domestic laws of the regional countries, may provide opportunities for developed and developing countries to strengthen cooperation and partnership to attain ambitions and goals of sustainable development through protecting and using their resources properly. Ultimately, we will find out that the development of the indicators is influenced by the significant impact of the policies of influential governments. 
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".