Nowhere to Play: Available Open and Green Space in Greater London Schools
Bibliographic record
Abstract
Experiencing outdoor space, especially natural space, during childhood and adolescence has beneficial physical and mental health effects, including improved cognitive and motor skills and a lower risk of obesity. Since school-age children typically spend 35-40 hours per week at schools, we quantified their access to open (non-built-up) space and green space at schools in Greater London. We linked land use information from the UK Ordnance Survey with school characteristics from the Department for Education (DfE) for schools in Greater London. We estimated open space by isolating land and water features within school boundaries and, as a subset of open space, green space defined as open space covered by vegetation. We examined the relationship of both school open and green space with distance to Central London, whether the school was fee-paying, and the percentage of pupils eligible for free school meals (as a school-level indicator of socioeconomic status). Almost 400,000 pupils (30% of all pupils in London) attended schools with less than ten square metre per pupil of open space-the minimum recommended area by DfE-and 800,000 pupils attended schools with less than ten square metre per pupil of green space. Of the latter, 70% did not have any public parks in the immediate vicinity of their schools. School green space increased with distance from Central London. There was a weak association between the school-level socioeconomic indicator and the amount of open and green space. Fee-paying schools provided less open space compared to non-fee-paying schools in central parts of London, but the provision became comparable in suburban London. Many London schools do not provide enough open and green space. There is a need to ensure regular contact with green space through safeguarding school grounds from sales, financially supporting disadvantaged schools to increase their outdoor space and providing access to off-site facilities such as sharing outdoor space with other schools.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".