Exams or applications? Elite Taiwanese students’ perceptions and navigation of college admissions systems
Bibliographic record
Abstract
Studies often portray elite students as self-interested adolescents who justify educational selection systems that favor them. However, this perspective neglects critiques of the college admissions system on the part of the elite, who often have no other option than to support it as fulfilling the ideals of fairness. This study examines academic elite students’ perceptions of college admissions systems when they are given choices as to which system to use. Data for this study come from surveys, interviews, and participant observation in Taiwan, where students are selected through two systems: exam-based selections and application-based selections. The findings show that students in elite high schools perceive whichever system that benefits them to be the fairest. By narrowly defining fairness as family influence on admission outcomes, these students downplay the institutional advantages they enjoy and present themselves as deserving candidates. Using the example of elite Taiwanese students, this study highlights that elites justify privilege based on self-interest and strategically navigate admissions systems to accrue advantages.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".