Administrative and Legal Regulation in the Field of Subsoil Use in Ukraine and Foreign Countries
Bibliographic record
Abstract
The article is devoted to the study of the features of administrative and legal regulation in the field of subsoil use. The essence of the category of administrative and legal regulation, as well as the mechanism of administrative and legal regulation in the field of subsoil use, is revealed. The legal basis of state regulation in the field of subsoil use in some foreign countries, in particular, in North America (for example, USA, Canada), European countries (for example, France, Germany) and CIS countries (for example, Kyrgyzstan and the Republic of Kazakhstan) are determined. Given the study of foreign practice of administrative and legal regulation in the field of subsoil use, the experience of the Republic of Kazakhstan has been recognized as positive, in particular, on the normative enshrinement in the Subsoil Code and subsoil use of basic principles in the field of subsoil use. Administrative and legal regulation in the field of subsoil use in Ukraine has been investigated by studying the legislative and organizational components. In the context of the above, it has been found that the regulatory framework for the implementation of state regulation in the field of subsoil use in Ukraine has a large number of regulations (both legal and substatutory). The system of state regulatory bodies in the field of subsoil use is represented by bodies of state power and local self-government, whose powers to use subsoil are determined by the norms of current Ukrainian legislation. The author's definition of the essence of the concept “administrative and legal regulation in the field of subsoil use” is given.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".