Improving the conceptual approaches of the state to the national resilience system
Bibliographic record
Abstract
The article provides a comprehensive analysis of conceptual and institutional approaches to the development of a national resilience system in the context of a transforming security environment. Special attention is paid to the role of local self-government bodies in ensuring national resilience at the basic level, considered through the prism of European countries’ experience. Best practices for integrating local structures into risk management systems, emergency response, adaptation, and post-crisis recovery are analyzed on the examples of countries such as Israel, Sweden, Estonia, Finland, Canada, and the Netherlands. The study demonstrates that an effective national resilience system requires a clear legal framework, institutional flexibility, digitalization of processes, interagency coordination, and the active involvement of civil society. Emphasis is placed on the need to develop an integrated resilience model that includes regional crisis centers, national digital monitoring platforms, public-private partnership mechanisms, and strategic training programs for civil servants in crisis management. Based on the analysis of international experience, it is established that involving local self-government bodies in the resilience system enhances the adaptability of the state and increases public trust in institutions. In particular, it is proposed to implement a territorial defense model at the local level (Israel), integrate digital crisis coordination systems (Estonia), develop a comprehensive national resilience program (Sweden), introduce crisis management certification (Finland), and establish a national risk scenario bank (Canada). The Ukrainian context is also described — legal acts such as Presidential Decree No. 479/2021 and Cabinet of Ministers Order No. 1025-r outline the strategic framework for shaping national resilience policy. The need for further detailing of implementation mechanisms, including at the local level, is emphasized to build a holistic, effective, and dynamic resilience management model. In conclusion, national resilience is seen not only as the ability to prevent threats but also as the capacity to maintain functionality under uncertainty, adapt, and recover quickly. This requires an updated state strategy based on openness, cooperation, and the integration of European security approaches.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| 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".