МЕХАНІЗМИ УЧАСТІ ГРОМАДЯН У ПУБЛІЧНОМУ УПРАВЛІННІ: ДОСВІД ЗАРУБІЖНИХ КРАЇН
Bibliographic record
Abstract
Topicality. Considering Ukraine's aspiration to become a full member of the European Union and participate on equal terms with other European states in defining global policies and goals for the future, the effective functioning of public participation mechanisms in governance is not only a goal for Ukraine, but also a requirement of the EU. In this sense, it is appropriate to investigate the peculiarities of the functioning of the mechanisms of citizen participation in public administration in different states, evaluating their experience and taking into account the principles and ideas that can be useful in reforming the Ukrainian legal system in this direction. The purpose of the article. Analysis of foreign experience of regulatory and practical support for the functioning of mechanisms of citizen participation in public administration, determination of advantages and disadvantages of various models of setting up government-public communications, as well as an outline of prospects for the development of mechanisms of public participation in state administration in Ukraine. Methods of analysis. The research uses general scientific and special methods of scientific knowledge. The purpose and tasks of the research include analysis and synthesis of information, comparison of foreign approaches to understanding public participation and its mechanisms, as well as formulation of the author's conclusions on specific issues, recommendations for theoretical and practical use. The results. The theoretical and practical aspects of ensuring the effectiveness of citizens' participation in public administration are analyzed. The standards in this area, the best foreign approaches and practices, and promising directions for the development of participatory democracy in Ukraine are outlined. Prospects for further research. The findings contained in this study can be applied during the improvement of national legislation and the implementation of regulatory provisions on effective public influence on public administration. In the future, it would be appropriate to pay attention to the peculiarities of ensuring the functioning of the mechanisms of citizen participation in the management of state affairs in other countries, in particular in Asian countries, Canada, the USA, etc.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".