Women Leaders of Higher Education: Female Executives in Leading Universities in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nowadays it is common for women to serve as university presidents and other high-level officials. Many women undertake leadership of universities, shouldering the important responsibilities of managing universities and promoting the construction and development of these institutions. This article investigates the female leaders in 38 leading universities in China. Leaders in the study are defined as presidents, vice-presidents, party secretaries and deputy party secretaries, as executive leaders and party leaders have similar ranks and authority within universities in China. By investigating their personal characteristics, this article draws an overall portrait of female leaders in leading universities in China. They are on average 54 years old, have high educational and academic achievement, are promoted principally from internal channels, most of them are deputies, and women on higher positions are more likely on the party track rather than the executive track. This article also discusses the role of female leaders in the field of higher education.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it