Bibliographic record
Abstract
In January 2019 around 176,000 pupils attended 163 grammar schools in England.Under the School Standards and Framework Act 1998 no new maintained grammar school can be opened, and existing schools cannot introduce new selection.However, there has been a very gradual but steady increase in the proportion of pupils at existing grammar schools over the past 30 years.This is because the average size of grammars has increased.The number of state grammars peaked at almost 1,300 in the mid 1960's.At this time around a quarter of all pupils in state secondaries attendended grammars.The number of grammars started falling soon after.The fastest period of decline was the 1970s; between 1971 and 1978 650 grammar schools closed.Grammars are unevenly distributed, with 75% of LEA's having no grammars. GCSE attainment at grammars is, on average much better than in non-selective schools.However, differences in pupil intakes means that headline results may not give us the most meaningful comparisons.As well as differences in prior attainment, pupils in grammar schools are much less likely to have special education needs or be eligible for free school meals compared to pupils in non-selective schools.Grammars have a slightly higher proportion of non-white pupils.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.139 | 0.112 |
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".