The meaning of play among children
Bibliographic record
Abstract
The purpose of this study was to investigate the meaning of play from children's perspectives. Children were recruited from a public suburban school in Alberta. Thirty eight students from grades 2-4 participated in group interviews. During the interviews each child created a collage from various materials (i.e., drawing materials, stickers, images) in response to four questions about play. Throughout the creation process the researchers talked to each child individually about their collage and their ideas about play. Next, each child presented and explained their collage to the whole group. The final portion of the session consisted of asking the entire group questions about play. All interviews were transcribed verbatim and analyzed using qualitative content analysis. Findings indicated that children classified a wide range of activities as play, including video games, structured and unstructured outdoor activities, and imaginative and 'make believe' games. However, television viewing, including watching movies, was generally not considered to represent play. Most children perceived that their meaning of play was different to adults. Themes relevant to what, who, and where children play were also explored. For example, children indicated they did not always like playing with their siblings and, although they liked playing indoors, they usually preferred outdoor play. These findings suggest the term play has broad and varied meanings for children. Thus, practitioners and researchers interested in increasing children's play or further exploring it as a means of physical activity need to define clearly how the term is used.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".