International experience of institutional support for small business in conditions of economic imbalances
Why this work is in the frame
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Bibliographic record
Abstract
This article examines the international experience of institutional support for small businesses under conditions of economic imbalances, with a particular focus on practices in the European Union, the United States, Canada, and South Korea. The study highlights the role of institutional mechanisms in ensuring the resilience of SMEs during crisis shocks such as the COVID-19 pandemic, energy instability, and structural transformations. It analyzes financial, regulatory, and partnership tools for supporting small businesses across centralized, decentralized, and network-based governance models. Special attention is given to the development of a prospective institutional policy model for SME support in Ukraine, taking into account the country’s post-war recovery needs and limited fiscal space. The purpose of the article is to conduct a systematic analysis of the international experience in institutional support for small enterprises under economic imbalances—focused on practices in the EU, USA, Canada, and South Korea—in order to identify effective policy models and financial-regulatory tools for SME support, and to develop proposals for their adaptation to Ukraine’s socio-economic conditions amidst ongoing war-related and post-crisis challenges. Methodology. The research applies methods of comparative analysis, structural-institutional approach, content analysis of official SME support programs, and elements of strategic planning to elaborate an adaptive model of institutional policy. Results. The study finds that the most effective models of SME support combine financial inclusiveness, digital service delivery, regulatory sensitivity, and public-private synergy. For Ukraine, the article proposes institutional transformations such as establishing an SBA-type agency, implementing the SME-test, expanding regional SME support centers, and launching public-private startup accelerators. This model is deemed capable of fostering SME resilience, innovation, and competitiveness under martial law and during the post-crisis recovery period.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it