Countermeasures Research on Developed Countries Using Intellectual Property to Promote the Development of Strategic Emerging Industries
Bibliographic record
Abstract
The strategic emerging industry is the industry that emerges in one country or region along with the implementation of technical innovation achievements and has strategic effects on economic and social development. To develop the strategic emerging industries is a significant action to promote the upgrading of industrial structure and transform the pattern of economic growth, as well as a strategic option for following the new scientific and technological revolution and dealing with the international financial crisis. For Japan, the U.S., Germany, and other developed capitalist countries, the main experiences for the development of strategic emerging industries are: highly integrate the intellectual property strategy with the development strategy of strategic emerging industries, apply the dynamic management, and smoothly connect the new ideas of the strategic emerging industries with the new market. In China, in order to develop the strategic emerging industries, we should learn from the successful experiences of developed countries, draft the promotion strategy of intellectual property at the national and industrial levels, provide protections for the development of strategic emerging industries, and effectively promote the development of strategic emerging industries.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".