Competing institutional logics of academic personnel system reforms in leading Chinese Universities
Bibliographic record
Abstract
This study utilises an institutional logic perspective to explore the dynamics and complexity of academic personnel system reforms at leading Chinese universities. Semi-structured interviews were conducted with 32 participants from 10 highly ranked universities; these interviews obtained the views of key observers on four main reform initiatives: global recruitment, the adoption of a tenure-track system and improvements to performance criteria and review procedures. Findings reveal that the fundamental goal of academic personnel system reforms for leading Chinese research universities was to address increasing global competition and stimulate research outputs within a new managerial context. A unique ‘two-tier’ career system is emerging influenced by the interweaving of competing logics and complicated interactions between external influences and Chinese traditions, in which the traditional permanent employment system operates simultaneously with the newly introduced tenure-track system, and ‘up-or-out’ has transformed into ‘up-or-transfer’ due to the legacies of the danwei system.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| 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".