Playspaces within playspaces: exploring children's experiences of play occupation within playgrounds
Bibliographic record
Abstract
Presentation given at the Inaugural World Occupational Science Conference in Vancouver, 2022 (Home - Inaugural World Occupational Science Conference (ubc.ca)). ABSTRACT Public playgrounds located in the neighborhoods are one place where children with different backgrounds and needs can meet, play, socially interact and connect with each other. Children report that playgrounds are important places in their lives. As such, playgrounds could be seen as collective spaces in a community setting. However, little is known about specific playspaces in playgrounds, what children do in these places and what meaning they ascribe to these places. Thus, the presentation aims to explore children’s doings in different playspaces on playgrounds, and the meaning they associate with these places. The presentation is informed by systematic search and synthesis of qualitative evidence about playgrounds from diverse children’s perspective. The included literature is analyzed through an occupational science lens and place-attachment theory. The findings will illustrate the different occupations children do in different places on playgrounds, and the meanings the children associate with it. Furthermore, children’s doings in these places are described and explored in relation to social interactions. Looking at playspaces from a child's perspective often gives insight into a different understanding compared to an adult's perspective. Within an Occupational Science community few have looked at specific playspaces on playgrounds and explored children’s occupations in these places from a place-attachment perspective. Therefore, the findings will add to the knowledge of children’s occupations as they are shaped by environmental relationships on playgrounds.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".