Environmental equity is child's play: mapping public provision of recreation opportunities in urban neighbourhoods
Bibliographic record
Abstract
This paper examines the spatial distribution of recreational opportunities for children and youth in a mid-sized Canadian city (London, Ontario), in relation to the socioeconomic status of neighbourhoods and estimated local need for publicly provided recreation spaces. Public recreation facilities (N = 537) throughout the city were identified, mapped and analysed in a geographic information system. To explore potential socio-environmental inequities, neighbourhoods (N = 22) were characterized by socioeconomic and environmental variables, an index of neighbourhood social distress, a neighbourhood play space needs index, and measures of the prevalence and density of recreational opportunities. The results of the spatial analysis indicate there is no systematic socioenvironmental inequity with respect to the prevalence and density of publicly provided neighbourhood recreation spaces; however, there are several areas in the city where youth do not have access to formal play spaces. We argue that to promote physical activity among urban children and youth, city planners and health policy analysts should consider carefully the geographical distribution of existing recreational opportunities and ensure that new publicly funded recreation spaces are provided to neighbourhoods with the greatest need. Further research should seek to identify what kinds of recreation spaces are most effective for promoting healthy behaviours among vulnerable children and youth.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".