Chinese Higher Education: The role of the economy and Projects 211/985 for system expansion
Bibliographic record
Abstract
Abstract China has experienced a significant economic growth in recent years. In addition, the country has also built the largest system of Higher Education in the world. However, was the economy that stimulated the advancement of Higher Education? Or was Higher Education that stimulated the advancement of the economy? To answer these questions, this research aimed to understand the role of economy and Projects 211 and 985 for the expansion of Chinese Higher Education. For that, an exploratory and qualitative research was developed, based on interviews with Chinese government managers and questionnaires applied to professors/specialists and to a student leadership. The results showed that investments in Higher Education were preponderant for the country’s economic growth, which was representative from a quantitative perspective. However, also aiming at qualitative growth, projects 211 and 985 were created, allocating a significant amount of resources to the selected institutions. Such positioning makes China an example of benchmarking for other countries that wish to progress economically and intellectually.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".