What determines PhD graduates’ employability in Chinese academia? A graduate capital perspective
Bibliographic record
Abstract
Chinese academic labour market is increasingly competitive, yet the factors shaping PhD graduates’ employability remain under-explored. This study investigates how PhD graduates in the humanities and social sciences, including both domestic PhDs and PhD returnees, mobilise different forms of capital in seeking employment in Chinese academic labour market. Drawing on Tomlinson’s graduate capital model and Bourdieu’s concepts of capital, field, and habitus, we conducted qualitative interviews with 27 Chinese early-career academics (11 domestic, 16 returnees). Findings reveal that employability is relational, stratified, and context-specific rather than individual possession. Human and cultural capitals are crucial, while social capital often proves decisive, disadvantaging returnees unfamiliar with domestic networks. Identity, psychological, and economic capitals mediate self-presentation and opportunity, while structurally contingent ‘fortune’ shapes access in unpredictable ways. Extending Tomlinson’s framework, this study theorises PhD graduate employability as dynamic and field-dependent, with implications for policy reform, institutional support, and equity in academic hiring.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".