Secondary school grades and graduate returns to education in the UK
Bibliographic record
Abstract
We examine the relationship between secondary school attainment and early-career graduate salaries in the UK. Based on literature on grade inflation, we hypothesise that there is uncertainty regarding the quality of the signal communicated by degree classifications, and that secondary school grades can be used as a tool to determine the veracity of classifications. We find that differences in secondary school attainment, expressed in UCAS points, are consistently a significant predictor of salary differences among graduates attaining Upper-Second-class degrees, and some First-class graduates. We estimate predicted probabilities, to predict the likelihood of a graduate appearing in a given salary band based on the combination of their secondary school attainment, degree classification and the university attended. The most common category of graduate in our sample (250 to 325 UCAS points, studied at a Post-1992 institution and attained an Upper Second class) has a 55% chance of attaining a salary less than £20,000 in the 12 months after graduation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".