Bibliographic record
Abstract
Chinese higher education policy has followed a fluctuating path determined by the twists and turns in the politics of the post-1949 Chinese state and that was particularly the case in the pre-reform era (1950s-1970s). This article, through investigating the changes of leadership that have occurred in Chinese universities and the duties of university administrators, examines the zigzag course which Chinese higher education policy has followed, identifying the model that shaped China’s higher education during the period from the 1950s to the 1980s. It also looks at what changes have taken place in China’s higher education since the 1980s, putting the pre-reform model in a broader context of China’s educational development. The article argues that the post-reform model for China’s higher education has functioned primarily in setting the political limits for the professional and commercial development of higher education in the course of China’s market-oriented reforms. In comparison with this political boundary-based model, the Chinese higher educational model during the period from the 1950s to 1980s could be identified as a management-oriented model. Not only did it set political limits but it also played an active role in informing the important managerial practices involved in the operation of Chinese universities.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".