Правові засади відновлення рослинного світу на територіях, пошкоджених внаслідок воєнних дій в Україні
Bibliographic record
Abstract
The article presents a comprehensive study of the legal framework for restoring Ukraine’s plant life in territories affected by the armed aggression of the Russian Federation. Emphasis is placed on the exceptional importance of vegetation as a fundamental structural element of ecosystems, on which the stability of the natural environment, the maintenance of biodiversity, the regulation of climatic processes, and the assurance of food and environmental security depend. It is shown that large-scale hostilities have led to the destruction of vegetation cover, soil degradation, the loss of natural landscapes, disruption of the water balance, and the extinction of rare and endemic plant species listed in the Red Data Book of Ukraine. A significant part of the territories of the nature reserve fund, which are of national and international ecological importance, has been severely damaged. The study highlights that the current environmental legislation of Ukraine does not provide a comprehensive legal regulation of vegetation restoration processes in territories affected by war. The Law of Ukraine “On the Plant World” and other normative legal acts contain only general provisions on flora protection, without defining the procedures for damage assessment, stages of rehabilitation, responsible entities, or sources of financing. The absence of a single coordinating authority, a special register of degraded territories, and a state monitoring system for restored ecosystems has been identified. Based on the analysis of the provisions of the Convention on Biological Diversity (1992), the Kunming– Montreal Global Biodiversity Framework (2022), UN documents, and the United Nations Environment Programme (UNEP) guidelines, the authors substantiate the necessity of implementing international environmental rehabilitation standards into Ukrainian law. The article also proposes key directions for improving legislative regulation in this sphere. Special attention is devoted to the concept of “green reintegration” as a new strategic direction of Ukraine’s environmental policy. This concept combines infrastructure reconstruction with the principles of sustainable development, energy efficiency, conservation of natural resources, and biodiversity restoration. The implementation of this approach will ensure synergy between environmental, economic, and social dimensions of Ukraine’s post-war recovery.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".