Storying the inclusive playground experiences of families of disabled and non-disabled children
Bibliographic record
Abstract
Playgrounds are proposed by scholars to hold a critical role in children’s health and sense of belonging. However, the built and social environments of playgrounds are often not prioritized for the full inclusion of disabled children. In this study, we explore ableism in children’s geographies of play through the research question, ‘What does the play journey look and feel like for families of disabled and non-disabled children on playgrounds that are intentionally designed for disability inclusion?’ Interviews with disabled and non-disabled children and their families (parents and siblings) at four playgrounds were used to produce a storied account of the nuances of the playground visit for families of disabled children. The story plot was determined using a digital storyboard process, thematic analysis, and collaborative writing that include three themes: parent labour, family connections, and rich play experiences. Central to the story is a relational experience of disability inclusion on playgrounds; one in which all members of the community, and not solely families experiencing childhood disability, are responsible for facilitating. Future directions include education and awareness raising among non-disabled families and the broader community for inclusion in public play spaces.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".