Empirical Study on Key Influencing Factors of Energy Efficiency of Scientific and Technological Achievement Transformation in Higher Vocational Colleges and Universities Based on Big Data Analysis
Bibliographic record
Abstract
Promoting the output and transformation of scientific and technological achievements of higher vocational colleges and universities is not only the topic of promoting the high-quality development of education in higher vocational colleges and universities, but also the way to deeply implement the innovation-driven development strategy.Taking higher vocational colleges and universities in four municipalities directly under the central government as research samples, this study first utilizes the DEA model to measure the transformation efficiency of scientific and technological achievements of higher vocational colleges and universities in four municipalities directly under the central government in the period of 2014-2023, and combines with the literature analysis method to dig out the key influencing factors of their transformation energy efficiency.Then, the fuzzy set qualitative comparative analysis method (fsQCA) is used to carry out empirical research on the transformation efficiency due to inputs and outputs of scientific and technological achievements of the studied higher education institutions and the interactions between their influencing factors, so as to analyze the grouping path of the improvement of the energy efficiency of the transformation of scientific and technological achievements of the higher vocational colleges and universities.In the analysis of the results of measuring the efficiency of the transformation stage of scientific and technological achievements, the efficiency of the transformation stage of scientific and technological achievements of local higher vocational colleges and universities in D city is generally at a high level, with an average value of 0.427.Meanwhile, regional development factors (consistency 0.9081>0.9)and policy factors (consistency 0.9322>0.9)are the necessary conditions for the efficient transformation of scientific and technological achievements of higher vocational colleges and universities, and they are the key influences to improve the energy efficiency of scientific and technological achievements transformation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".