Компаративный анализ подходов к организации финансирования стратегии инновационного развития национальных экономик за рубежом
Bibliographic record
Abstract
The transition from commodity development model to the model of innovation development of economy is a major landmark in the sustainable development of the national economy through diversification and modernization of the economy, creation of conditions for production of competitive products, export growth. Full development of innovations in recent decades became one of the main national priorities in the leading Western countries. The rapid growth of the volume of financing of the strategies of national economy innovative development proves that. The emerging multipolar world had 4 main centers of scientific advance by 2011: United States (31 % of the world's research and development spending by purchasing power parity), the European Union (24 %), China (14 %) and Japan (11 %)/ The world leader in absolute terms for the strategy of innovative development financing are traditionally the United States. In 2012, the United States assigned 418.6 billion dollars for this purpose, which is over a third of the total annual investment in research and development in the world (1.1 trillion dollars). In recent years, China has been second in terms of funding for the strategy of innovative development of the national economy in absolute terms, Japan third. Unfortunately, the Russian Federation is not in the group of leaders with less than 2 % of the world's expenditure on research and development in terms of purchasing power parity and 1 % by exchange rate. In the innovation economy, the share of the private sector in the financing of research and development is high: in the United States it is 67 %, Germany 64.1 %, Canada 49.4 %, France 48.5 %. The forms of public-private funding of large projects are diverse, while in Russia this figure is twice lower. The global market of research and development by the financial indicators of 1000 largest investors in research and development of 2013 amounted to 635 billion dollars. Among the companies with the greatest costs of research and development are Volkswagen, Samsung, Roche and Intel. In general, analysis of the data of thousands of the world's largest companies on innovation costs has shown that in 2013 the research and development costs rose to a record 635 billion dollars. Corporations with headquarters in North America have increased budgets by 9.7 %, European by 5.4 %, while Japanese only by 2.4 %. Research costs of Indian and Chinese companies have rapidly grown by 27 %. The main task of Russia today is the creation of a successful innovation climate in society as a whole, and the addition of soft stimulating financial measures to the State support for innovation costs, industrial enterprises and infrastructure.
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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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".