The Impact of Knowledge Spillover from Universities in Sichuan-Chongqing Region on Regional Innovation Capacity
Bibliographic record
Abstract
As an important subject of the regional innovation system, the scientific research activities of universities are not only the power source of talent cultivation and knowledge innovation but also an important force to promote regional innovation development. This paper examines the influence relationship between knowledge spillover from universities in Sichuan province and Chongqing city and regional innovation capacity from the aspects of teaching and research personnel input, research and development personnel input in research input, monographs, academic papers, technology transfer contracts and transfer income in research output. The results show that the improvement of the innovation capacity in Sichuan province and Chongqing city depends on the increase of teaching and research personnel input and the number of scientific and technological topics in universities, while other indirect scientific research results do not contribute significantly to the regional innovation capacity; further mechanism analysis reveals that the knowledge spillover from universities mainly promotes the improvement of regional innovation capacity through human capital, physical capital, and scientific and technological innovation.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".