Innovation as a Vector of Regional Economic Development and a Necessary Condition for the Progress of the World Economy
Bibliographic record
Abstract
Innovative development is an essential component of economic development, responding to global challenges of our time. Please be aware that nowadays there is a great increase of not only the practical implementation of innovative technologies and processes, but also of theoretical understanding of these trends in theoretical studies. Exploring the nature of innovation processes and factors of their incentive economics focuses on the large-scale process of generating ideas and theories, issues of priority, issues of innovation, and economic and cultural backgrounds’ need for innovative ideas. Innovation is the result of the transformation of ideas, research, development, new or improved scientific and technical, socio-economic, political and other decisions that promote, improve the quality and standards of living of the population and national security through the harmonization of the economic interests of economic entities (profit firms), market of consumer interests (needs at the lowest cost) and interests of society (rationalization needs, environmental protection, reduction of unemployment, the growth of the tax base, increase in average household incomes, reducing their differentiation, growth of intellectual potential of society, increase in life expectancy, increasing competitiveness of regions, countries and so on. Therefore, it is necessary to identify the role of innovation in the development of regional and global economy, which this study is dedicated to.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".