РОЗВИТОК МЕТОДОЛОГІЧНОГО ПІДХОДУ ЩОДО ІНТЕГРУВАННЯ ПРИРОДНИХ АКТИВІВ У СИСТЕМУ УПРАВЛІННЯ МУНІЦИПАЛЬНИМИ АКТИВАМИ
Bibliographic record
Abstract
The purpose of the research is to substantiate the development of a methodological approach to the integration of natural assets into the municipal asset management system, in the context of adapting the best world experience to the specifics of Ukrainian municipalities. The research methodology includes a descriptive analysis and consideration of cases regarding the natural asset management, primarily at the municipal level, in particular in accordance with the advanced Canadian MNAI methodology, within the framework of substantiating the features of the integration of natural assets into the municipal asset management system. According to the results of the conducted research, in particular within the analysis of the materials of the Recovery Plan of Ukraine, it was revealed that the situation with the infrastructure of the life support systems of cities and other settlements is significantly complicated due to the russian invasion: destroyed / damaged drinking water supply and drainage systems, these systems are overloaded in the western regions of the country, the quality and safety of drinking water do not meet the requirements for suitability for human consumption, etc. The MNAI methodology, identified as optimal for implementation in the cities of post-war Ukraine, contributes to ensuring the motivation of local self-government bodies to make informed decisions about how to manage a specific natural asset so that it can provide the specified services on an ongoing basis. Planning and management tools include operation and maintenance plans, which ideally will provide local governments with a practical operational framework for the long-term natural asset management. The implementation of this methodology involves the realization of projects based on partnership. The obtained results of the research can be projected into the plane of implementation of nationwide long-term projects relevant to the municipal natural asset management in Ukraine
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.019 |
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; both teacher heads agree on what is shown here.
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".