Prospects for the Development of Venture Capital as an Economic Institution in Post-Soviet Countries
Bibliographic record
Abstract
The development of venture capital in the post-Soviet countries has features of its historical formation.This field of activity is relatively new in the region, although it has deep roots in the history of such developed economies as the United States, the European Space, and Japan.However, the relevance of the research lies in the study of this phenomenon in the region of Central Europe, Asia, and the Caucasus.The paper aims to assess the benefits, risks, and prospects associated with venture capital in the post-Soviet space.The methods and materials used in the study included statistical material processed with statistical programs (SPSS) and mathematical modeling of forecasting results; calculations of economic indicators (ROE, IRR) and the level and required size of venture capital for business development; and the consideration of hypothetical situational models and the level and number of innovations.The chaotic and unstable development of the economic state of the EECCA countries creates various contradictions.Nevertheless, the study confirms the need for venture capital as a driving factor in the development of these economies.This research also covered such categories as crowdfunding and angel investors at the initial stages, even before venture investment.The results of the study find practical applications in stimulating business organizations that, for various reasons, search for new business methods.Venture organizations encourage entrepreneurs to open new business units to solve existing problems in society and various spheres of its functioning.These also organizations motivate investors to promote innovative enterprises in the developing economies of the studied region.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".