FOREIGN EXPERIENCE IN STIMULATING ENTREPRENEURSHIP IN THE MANUFACTURING INDUSTRY
Bibliographic record
Abstract
The development of the manufacturing industry is a key focus of economic policy in many countries striving for technological independence and sustainable growth. Under current conditions, Kazakhstan is also implementing an industrialization strategy, with particular emphasis on supporting entrepreneurial entities in the production sector. The aim of this article is to analyze international experience in promoting entrepreneurial activity in the manufacturing industry and to identify the potential for adapting these approaches to the socio-economic context of Kazakhstan. The study examines approaches applied in the United States, Canada, South Korea, and Russia. Special attention is given to such support instruments as tax incentives, concessional financing, subsidies, innovation and cluster programs, production digitalization, and infrastructure development for small and medium-sized enterprises (SMEs). A comparative analysis of the effectiveness of these measures is conducted, and practices with potential applicability to the Kazakhstani context are highlighted. The article substantiates the need for institutional strengthening, regional differentiation of support measures, and enhanced cooperation among business, science, and government. The findings of the study can be used in the development of state programs for entrepreneurship support, industrial development strategies, and import substitution mechanisms in the Republic of Kazakhstan.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| 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; 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".