How are Chinese Students Ideologically Divided? a Survey of Chinese College Students' Political Self-Identification
Bibliographic record
Abstract
Students have always played an important role in defining the politics of China, and their ideological orientation shapes the nature of student politics. Through a survey of students from six elite universities, this study explores the outlook of Chinese youth’s political identities and analyzes the factors conditioning their identity formation. The results reveal three trends. First, the majority of these college students either claim themselves to be apolitical or to be liberals. Second, among various channels of political (re)socialization, family plays a weak role, while mass media has a strong influence on students’ political orientation. Peking University, the base for nurturing liberals in the 1990s, has now yielded this role to universities specializing in economics and finance, thus suggesting the impact of economic liberalism since the 1990s. Third, gender, education level, academic major, family income and Communist Party membership arc all good indicators of students’ political identities. These results arc interpreted in the context of student movementsand intellectual transition in China over the past four decades.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".