Autonomy, Governance and the Chinese University 3.0: A <i>zhong–yong</i> Model from Comparative, Cultural and Contemporary Perspectives
Bibliographic record
Abstract
Abstract This article builds on the ambiguous concept of the autonomy of universities with three historical turns in two dominant types of universities in the world – the Anglo-Saxon and American models, represented by the British and American institutions, and the Continental models, including the recently emerging Chinese University 3.0. Based on empirical data from two comparative case studies with a documentary analysis approach, I investigate the structure of the zhong-yong model of self-mastery, demonstrating how it may differ from the Western models and offering cultural interpretations for these nuances. The article concludes that self-mastery in the Chinese context provides an additional form of autonomy which is rooted in the pragmatic Confucian concept of zhong-yong. It is also found that through the pragmatism of self-mastery, the zhong-yong model enables Chinese universities to directly serve the state and, at the same time, to legitimate the priority given to their development by state power, thus creating abundant space and resources for them to fully unfold their potentialities. With multilayered and multidirectional power relationships, this model of governance has enabled Chinese universities to radically transform themselves in a short period of time and will allow them to eventually become global leaders, although they may have to sacrifice autonomous freedom in some ways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".