Neighbourhood, built environment and children’s outdoor play spaces in urban Ghana: Review of policies and challenges
Bibliographic record
Abstract
Although a great deal of research work has been done by social scientists on walkability and playability, the focus to a large extent has been on the global north. Research work on the urban built environment and children's play has not engaged Africa in general and Ghana in particular. More importantly, there is limited evidence of policies in terms of community-based practices and governmental policies and programmes for the promotion of play. The limited effort in promoting physical activities have to a large extent focused on walkability, yet evidence to date indicates that walking only constitutes a small proportion of the physical activities of children. This is against the backdrop of growing urbanization and the increasing reported incidence of sedentary lifestyles, less physical activity and obesity among children and the youth. Our main objective in this paper is to contribute to the literature on Ghana, and by extension Sub-Saharan Africa, by examining the extent to which playability features in city and national policies and strategies in urban Ghana. We conclude that while there is dearth of public policies on children's play, with the situation in communities compounded by weak city government capacity to plan, implement and enforce development control to protect open spaces for children's play and recreational purposes. The paper recommends a change in policy and practice on creating spaces in urban built-environments for children's play in urban Ghana.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".