The fun factor: Adolescents’ self‐regulated leisure activity and the implications for practitioners and researchers
Bibliographic record
Abstract
There is mounting interest in Canadian society regarding the leisure activities of children and youth and the ensuing positive or negative effects. Complex influential factors on adolescent self‐regulated time coupled with increasing levels of sedentary activity have provoked a societal dilemma. Consequently, it is essential to determine the motivating factors in adolescents’ leisure choices in order to fully address the societal dilemmas involving youth inactivity. Understanding perceptions of “fun” by children and youth in relation to their leisure time formed the basis for this inquiry. Theoretically grounded in self‐determination theory, this study focused on fun‐provoking favourite activities among Grade 6 through Grade 8 students (n=220) at 13 schools across Ontario through surveys and interviews, as part of a larger study on children's media consumption. Also, the adolescents’ media consumption and physical activity patterns were examined in order to assess their leisure habits and gain insights into positive and effective programming for youth. The discussion includes dominant themes of “fun” in the adolescents’ lives. Implications for the development of a critical pedagogy are offered for researchers and practitioners in leisure education and physical education.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".