LEGAL REGULATION OF HUNTING BY FOREIGN CITIZENS IN UKRAINE, THE REPUBLIC OF BELARUS AND CANADA: A COMPARATIVE LEGAL ANALYSIS
Bibliographic record
Abstract
legal regulaTIOn Of hunTIng by fOreIgn cITIzens In uKraIne,The republIc Of belarus anD canaDa: a cOmparaTIVe legal analysIs summary.The article deals with results of investigation of the legal regulation of hunting of foreign citizens in the territory of Ukraine.The authors analyze the current legislation of Ukraine on this issue, in particular, the procedure for granting special permits, the restrictions and the procedure of hunting.The article also analyzes the legislation of the Republic of Belarus and Canada, in particular, the procedure for granting special permits, the period for which such permit is granted, the documents to be provided by a foreign hunter and payment for hunting.Regarding hunting by foreigners in the designated territories of these states, where this issue is more completely settled than in the law of our state.The urgency of the chosen topic is due to the fact that hunting of foreigners in Ukraine is quite common, however, in the current legislation of Ukraine there is no legal act that would stipulate the procedure of such hunting.It is create favorable conditions for the abuse of certain persons by their rights and the unregulated exploitation of natural resources.And, as a result, it can damage the animal and plant life of Ukraine as a whole.Currently, there is no detailed regulatory framework for hunting of foreign nationals in Ukraine.The authors substantiate the need for amendments to the current legislation of Ukraine, taking into account the experience of foreign countries in order to ensure the protection of wildlife.The purpose of this article is a systematic analysis of the legal framework, which is the basis for hunting of foreign citizens in the territory of Ukraine, as well as making proposals for changes and additions to the legislation of Ukraine in this field.In addition, an analysis of the main approaches of foreign countries in regulating this issue.
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 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 | 0.001 |
| 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) | 0.001 | 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 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".