Місцеве самоврядування і забезпечення соціальної справедливості: національний досвід і зарубіжні практики
Bibliographic record
Abstract
The article explores the role of local self-government in ensuring social justice as a fundamental principle of democratic society. Social justice is understood not only as equal access to social benefits but also as a real tool for shaping fair, inclusive, and sustainable territorial communities. The focus is placed on analyzing the current Ukrainian experience in this area, especially in the context of the decentralization reform, which has significantly expanded the powers and functions of local self-government bodies. Ukrainian communities are increasingly implementing social protection programs, adapting service delivery to local needs, and developing mechanisms for citizen participation. The article provides a detailed description of practices related to municipal assistance, social housing, inclusive education, medical services, and support for vulnerable groups. At the same time, systemic challenges are highlighted, such as financial disparities among communities, lack of qualified personnel, and limited legislative capacity at the local level, which hinder the full realization of the principles of social justice. In the context of comparative analysis, the foreign experiences of European Union countries (Germany, Sweden, France, Poland) and North America (Canada, the USA) are presented, where local self-government plays a leading role in social policy. The article outlines key models of social service organization, funding sources, partnerships with civil society institutions, participatory governance practices, and the adaptability of social programs. Special attention is paid to tools for assessing social impact, involving citizens in decision-making, and integrating justice principles into municipal budgeting. The experience of developed countries shows that the effectiveness of local social policy depends not only on formal powers but also on real autonomy, financial stability, and the institutional capacity of communities to manage social processes. Based on the analyzed experience, the article formulates proposals for improving the Ukrainian model of ensuring social justice at the local level. These include expanding the financial base of local self-government, granting communities greater autonomy in shaping social policy, developing systems for monitoring and evaluating decision effectiveness, improving the professional qualifications of social sector personnel, and actively involving citizens in governance processes. The article emphasizes that only through a comprehensive approach and consistent state support can local self-government bodies become genuine guarantors of social justice within communities, contributing to sustainable development, social cohesion, and an improved quality of life for the population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.271 | 0.001 |
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".