An Analysis of Playground Equipment Accessibility for Children with Disabilities: A Case Study at Alun-Alun Depok
Bibliographic record
Abstract
Abstract This study evaluates the accessibility of playground equipment at Alun-Alun Depok, focusing on creating a more inclusive environment for children with disabilities, particularly those with visual impairments. The research aims to identify the barriers visually impaired children face when interacting with various play structures, such as swings, slides, climbing frames, and spring riders. Observations of children’s interactions with the play equipment were conducted alongside interviews with caregivers to gather insights on accessibility challenges and potential improvements. The findings highlight obstacles that limit safe and independent play for visually impaired children, emphasizing the need for sensory cues, tactile markers, and other adaptive design features. This study also explores how sustainability principles can be integrated into playground design, aligning with the United Nations Sustainable Development Goal (SDG) Target 11.7, which advocates universal access to safe, inclusive, and accessible public spaces by 2030. Recommendations are provided for enhancing the playground’s inclusivity while using durable, eco-friendly materials supporting long-term usability. By focusing on the intersection of inclusivity and sustainability, this research aims to contribute to a broader understanding of how urban public spaces can be designed to accommodate diverse needs. The study offers practical design guidelines that aim to create playgrounds where all children, regardless of ability, can enjoy equal opportunities for play and social interaction, promoting a more equitable and sustainable urban environment.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".