How Chinese high schools equip first-generation college students with capital for elite university admissions: an examination from the students’ perspective
Bibliographic record
Abstract
This study explores how Chinese first-generation college students (FGCSs) admitted to elite universities perceive their high schools’ roles in equipping them with essential capital for success in an exam-based selection system. Based on qualitative interviews with 21 FGCSs from two elite Chinese universities, the research identifies four forms of capital developed through specific high school practices: (1) routinisation of test-taking habits to develop learning capital, (2) symbolisation of rankings and hierarchical tracking as ‘success’ to foster aspirational capital, (3) promotion of school-mediated connections to enhance social capital, and (4) cultivation of interpersonal care and support to build emotional capital. While these practices support university admissions, they also introduce mental health challenges and overlook the students’ needs for holistic development. This study contributes to the international discourse on disadvantaged students in elite university admissions by examining both the benefits and limitations of China’s exam-focused schooling 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".