Bibliographic record
Abstract
The article explores the current state of social entrepreneurship in Ukraine and analyzes effective mechanisms of state support for this sector. Emphasis is placed on the formation of a favorable legal environment, particularly the development of a legislative framework that provides a clear definition of social entrepreneurship and establishes criteria for receiving state support. Tax incentives are examined as a means of reducing the financial burden on social enterprises, including reduced corporate tax rates, exemption from value-added tax (VAT), and the introduction of tax holidays for newly established enterprises. The significance of financial support, such as grants, subsidies, and preferential loans, is substantiated as essential tools for providing resources for the creation and scaling of social projects. The importance of educational initiatives is highlighted to enhance the competencies of entrepreneurs, as well as informational support to raise public awareness about the benefits and opportunities of social entrepreneurship. The study underscores the critical role of state policy in addressing existing challenges, such as the lack of a unified legislative definition, limited access to financing, low societal awareness, and insufficient educational initiatives. Recommendations are proposed for adapting international best practices to foster the development of social entrepreneurship in Ukraine. The analysis also emphasizes the potential of financial mechanisms, such as grants aimed at supporting specific social initiatives, subsidies to offset operational costs, and low-interest loans designed to facilitate enterprise growth. Drawing on international experiences from countries like the United Kingdom, Germany, Canada, France, and South Korea, the article demonstrates the effectiveness of integrated approaches to supporting social entrepreneurship. The adaptation of these practices to the Ukrainian context, considering its economic, legal, and cultural specificities, is identified as a key step towards creating a supportive ecosystem for social enterprises. Such measures are expected to enhance the sector’s capacity to address pressing social challenges, promote economic sustainability, and foster social cohesion in Ukraine. Keywords: social entrepreneurship, state support, legislative framework, tax incentives, grants, subsidies, financial mechanisms, international best practices, Ukraine.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".