Study on Cross-Administration Innovation System of the Yangtze River Delta
Bibliographic record
Abstract
Since the decentralization of China, regional governments have got more power on how to allocate their investment and set the performance criteria for economic sectors. Strengthened by the regional specific culture, geography and language, administration-based regional innovation system developed quite rapidly in China with great diversity. But with the development of the regional economy, when the traditional administrative division overemphasizes this local benefit to prevent innovation essential factors from flowing and restrict innovation efficiency, the innovation system must surmount the administrative division to carry on innovation in an appropriate region. According to analysis of the yearbooks of Jiang and Zhe provinces and Shanghai, we discovered that the Yangtze River Delta CARIS is a developing model that is a core impetus and supplementary coexisting model and meanwhile a circle proliferation model. Through the research of innovation system in the Yangtze River Delta, the establishment of CARIS is hardly needed in China for the reason of special administrative divisions. Meanwhile, some suggestions are given about how to promote the cross-administration innovation system.
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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 | 0.001 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".