ВПЛИВ СОЦІАЛЬНОГО ПІДПРИЄМНИЦТВА НА ЕКОНОМІЧНУ АКТИВНІСТЬ ВРАЗЛИВИХ ГРУП НАСЕЛЕННЯ
Bibliographic record
Abstract
The article explores the impact of social entrepreneurship on the economic activity of vulnerable population groups. Social entrepreneurship is an innovative activity that combines economic efficiency with achieving social goals. The study emphasizes the importance of social enterprises in addressing critical societal issues by creating jobs, providing professional training, and promoting social integration for marginalized groups, including persons with disabilities, internally displaced persons, single mothers, and the unemployed.The article analyzes international practices in developing social enterprises, highlighting the experiences of the United Kingdom, Germany, France, Canada, and South Korea, and identifies opportunities for adapting these best practices to the Ukrainian context. Special attention is paid to the role of social enterprises in fostering inclusive environments and overcoming barriers related to stereotypes and discrimination. The dual mission of social enterprises – ensuring financial sustainability and addressing societal challenges – is underlined as their distinctive feature compared to traditional business models.Key challenges facing social entrepreneurship in Ukraine are identified, including inadequate legislative frameworks, limited financial resources, and a lack of public awareness about the benefits of this sector. The study highlights the need for comprehensive measures to support social enterprises at the national level, including legislative improvements, tax incentives, and state-funded grants. The importance of introducing educational programs to develop skills and raise awareness about social entrepreneurship among entrepreneurs and the general population is also emphasized.Furthermore, the study emphasizes the importance of investment in social enterprises. Over the period analyzed, significant growth in employment within social enterprises, increased investment levels, and a rise in the number of active social enterprises were observed despite the challenging economic environment in Ukraine. These trends indicate the sector's resilience and potential for sustainable development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".