Who Should Go to University? Justice in University Admissions
Bibliographic record
Abstract
Current debates regarding justice in university admissions most often approach the question of access to university from a technical, policy-focussed perspective. Despite the attention that access to university receives in the press and policy literature, ethical discussion tends to focus on technical matters such as who should pay for university or which schemes of selection are allowable, not the question of who should go to university in the first place. We address the question of university admissions—the question of who should go to university—from an ethical perspective. We find that most discussions draw on a generic conception of what the university is good for that is too thin to provide deliberative guidance and hold that a full account of the ethics of admissions needs to take into account the distinctive good that the university provides—knowledge and understanding. This view, we hold, does not imply that measures should not be taken to widen access to university; however, the basis for such measures should be grounded in that distinctive good in the first instance.
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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 | 0.031 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.054 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".