STRUCTURAL AND LEGAL ANALYSIS OF SCIENTIFIC ACTIVITY REGULATION IN DEVELOPED COUNTRIES
Bibliographic record
Abstract
Experience of developed countries makes the case that it is possible to achieve a high level of competitiveness in the globalized market solely by using achievements of scientific-and-technological advance. National policy and effectiveness of means of scientific sector support used in the country are essential to it. The purpose of the article is an effort to perform the structural analysis of support, regulation, and financing of scientific activity in world's major economies, having determined central institutes of financial means command for the investment into innovative and scientific activity in the countries. To perform a functional analysis of the funded status of Ukrainian scientific and technological and educational activity from the standpoint of its public regulation. Based on the studied funding model of scientific activity in developed countries, to propose the model of optimization of scientific activity financing that will become the innovative activator of support and development of Ukrainian science. Analysing public policy of developed countries related to the support of scientific, educational, and innovative activity according to the degree of state regulation, it is possible to identify two poles. The first pole can be notionally named as English-American model where the state does very little to interfere with the activity of scientific and innovative sector. It is characterized by the fullest autonomy of entrepreneurship in the innovative and scientific and educational sphere. With the use of such model, it is assumed that market mechanisms facilitate acceleration of scientific and innovative processes of country development by them. The second pole, a Franco-Japanese model of public regulation, is characterized by the substantial impact of the state on scientific and educational processes, in particular, by non-market financing methods. With the use of this model, the governments determine priority guidelines of innovative and technological development supported by the government substantially; such countries to some extent include: France, Sweden, and Japan. Most of the developed European countries (Germany, Poland, Italy) and Canada are found in between specified poles of scientific and innovative policy while developing a national business environment and using direct state support of innovative activity. The increase in expenses of the private sector for research and development activities appears in all countries. Public authorities support scientific studies, innovative activity and development of small and medium-sized businesses in a scientific and technological sphere; they cooperate actively during the development and implementation of national programs. Moreover, other concerned parties -industrial companies, representatives of the academic community, non-governmental non-profit organizations -are involved more actively in the decision-making process. Max Planck Society in Germany can become the experimental model of regulation and financing of scientific, educational, and innovative activity of institutions. Implementation of a new economic model in Ukraine is possible upon the condition of creation and adjustment of the functioning of two closed and Baltic Journal of Economic Studies 148 Vol. 4, No. 3, 2018 related engineering processes: innovative and productive: education-science-production-market; investment. The following may be classified as top priorities of development of scientific and technological activity in Ukraine: prevention of arrival of earlier and inefficient technologies; facilitation of application of state-of-the-art highly efficient technologies, development of scientific potential and human resourcing; arrangement of conditions for extension and expansion in the number of innovative structures (technology parks, technopolis, business incubators, innovation centres, innovative exchange markets).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".