The iron law of hierarchy? Institutional differentiation in UK higher education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper maps the main dimensions of differentiation among institutions and ‘faculties’ (subject areas within institutions) of higher education in the United Kingdom. It does so through a principal components analysis based on the characteristics of applicants and entrants. A single status dimension accounts for a quarter of the variation, and is associated with the social class, educational background, age (under 21) and non-local origin of students. This dimension is very stable over time and across England, Wales and Scotland. It is robust in the face of alternative specifications. The paper argues that this institutional hierarchy is deeply embedded in wider social structures and reflects the social reproduction role of higher education. Other, somewhat less stable dimensions, are associated with students' ethnic background and domicile.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it