Analysis of foreign experience in stimulating innovation activities of small and medium-sized industrial enterprises as an element of strategic development of the state
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Bibliographic record
Abstract
В статье представлен анализ зарубежного опыта стимулирования инновационной деятельности малых и средних промышленных предприятий как элемента стратегического развития государства. Особое внимание уделено стимулированию инновационной деятельности промышленных предприятий стран Европы (Германия, Великобритания, Финляндия), Америки (США, Канада) и Азии (Япония, Китай, Южная Корея, Индия). Сделан вывод о том, что изученный опыт различен, имеет общие черты и особенности, а также может быть применен при разработке стратегии инновационного развития России. Выделены главные и основные особенности всех изученных методов. The article presents an analysis of foreign experience in stimulating innovation activities of small and medium-sized industrial enterprises as an element of strategic development of the state. Special attention is paid to stimulating innovative activities of industrial enterprises in Europe (Germany, great Britain, Finland), America (USA, Canada) and Asia (Japan, China, South Korea, India). It is concluded that the studied experience is different, has common features and features, and can also be applied in the development of a strategy for innovative development in Russia. The main and main features of all the studied methods are highlighted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it