THE INTERACTION BETWEEN LOCAL SELF-GOVERNMENT BODIES AND THE POPULATION AS A FACTOR OF EFFECTIVE GOVERNANCE
Bibliographic record
Abstract
The article examines the interaction of local self-government bodies with the population as a key factor in effective governance at the local level. It is argued that, under conditions of decentralization and the transformation of public administration, the role of local institutions in ensuring transparency, accountability, and social cohesion increases; the quality of communication between authorities and citizens affects the effectiveness of management decisions, trust in institutions, and community resilience in crisis situations. The theoretical part of the study defines the multidimensional concept of “interaction between local self-government bodies and the population” through three components: informational, consultative, and partnership, on the basis of which a general model is proposed that views citizens as active participants in policy co-creation. The methodological framework includes the analysis of international standards (in particular, the Open Government Directive and the IAP2 Spectrum of Public Participation), a comparative analysis of foreign practices (USA, Canada, EU countries), and an assessment of Ukrainian institutional realities in the context of decentralization and martial law (analysis of legal acts, implementation of digital platforms such as e-dem, and cases of participatory budgeting). The empirical part identifies key patterns: technological platforms significantly expand citizens’ access to information and participation, but their effectiveness depends on the institutional capacity of local self-government bodies; predominance of uniform forms of participation (informing, formal consultation) does not ensure sustainable engagement and results in low citizen influence on decisions; advancing levels of engagement (collaboration, empowerment) improves the quality of decisions and citizen readiness to participate in their implementation. For practical assessment of “quality” interaction, a criteria matrix is proposed that combines IAP2 Spectrum levels with normative values of public participation, as well as an indicator system for quantitative and qualitative monitoring (level of awareness, degree of citizen input impact, availability of feedback, institutional stability of engagement channels, trust index). Based on the results, practical recommendations are formulated: to standardize local regulations on interaction mechanisms; integrate digital platforms into decision-making systems with clear feedback procedures; promote the transition from formal participation to collaboration and empowerment in selected areas; develop institutional capacity of local self-government bodies (training, creation of communication positions/offices, methodological standards for “good interaction”); and foster partnerships with civil society institutions and international programs (UNDP, donor initiatives) to support community resource and expert needs, especially under martial law conditions.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".