Administrative Law in Sustainable Development: A Case Study of the Interaction Between Eco-Business and Government in Jordan
Bibliographic record
Abstract
The main purpose of the article is a modern methodological approach to identifying and countering key negative factors that impede effective interaction between business and government in the region in the system of legal support for sustainable development.The object of the study is the business environment of Jordan and the features of its functioning in the context of sustainable development.The scientific task of the article is to form a modern approach to identifying and countering administrative and legal methods, and key obstacles in the system of interaction between business and government in the context of sustainable development.The research methodology involves the use of modern methods of structured Analysis, pairwise comparison and graphical modelling.As a result of the study, key problems were identified that impede an effective system of interaction between business and government in the region in the context of sustainable development.The innovativeness of the research results lies in the formation of a modern approach to identifying and countering the key problems of an effective system of interaction between business and government through legal support for sustainable development.The article is limited by taking into account the specifics of only one country.Prospects for further research are aimed at expanding the through legal support for sustainable development and taking into account more Middle Eastern countries.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".