The quest for world-class universities in China: Faculty members' subjectivities in the era of globalization
Bibliographic record
Abstract
With the intensified forces of globalization and neoliberalism, the quest for world-class universities (WCUs) has become a high priority for governments around the world. Existing literature suggests that insufficient academic attention has been given to an examination of the complex policy enactment process (Ball, Maguire & Braun, 202), and in particular, how faculty members respond to the national agenda of building WCUs and how their understanding of higher educaiton and their subjectivities are shifting in the face of the enormous changes cased by globalization, neoliberal forces and specific cultural influences such as the national history, and socially transmitted behaviour patterns and beliefs. Through analyzing policy documents and artifacts, and conducting in-depth interviews with twelve faculty members from a key university in China, this case study examines how individual faculty members are being constituted and constituting themselves in the enactment of policy of building WCUs in China. Three sets of interrelated and complementary critical social theories are drawn upon in this study, and both interview transcripts and policy documents and
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".