Innovation Activity in the Republic of Kazakhstan: State Controlling and Ways to Increase Management Efficiency
Bibliographic record
Abstract
The main goal of the research is to reveal the dominant role of the state in the innovational development of the country and to define promising areas of the cooperation between the state, universities (research institutes) and industry in conducting the research activity. At the present time the innovation activity is a locomotive of progressive phenomena in the economy of the country. Herewith, it is noted that in the Republic of Kazakhstan innovation activity, according to its indicators, falls behind the desired efficient result. This article defines the level of the development of innovation entrepreneurship activity in Kazakhstan. It states the problems related to the innovation development due to the current tendencies of the development of economy in the world. It offers measures for stable and dynamic development of the country that includes the notion of the competitiveness and development of innovational schemes of development that are based on efficient interrelation and optimal combination of interests of the state, universities (research institutes) and private sector of Kazakhstan. On the basis of the conducted analysis of variables – factors of innovational development - it was revealed that the efficiency of managing innovation activity by governmental authorities was a “primal cause” that had an impact on such indicators as the level of development of innovational infrastructure and wealth of the country. The authors also proposed the measures of state regulation of the innovation development of enterprises and stimulation of partnership of the science with the production.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".