“I Just Want to Have Fun, But Can I?”: Examining Leisure Constraints and Negotiation by Children and Adolescents
Bibliographic record
Abstract
This study examined physically active leisure constraints of children and adolescents and empirically analyzed their ability to negotiate strategies to reduce their experience of constraints. Self-administered questionnaires and accelerometers were used to collect data on leisure constraints and physical activity from students (n=1654) in grades 3, 7, and 11. Gender and age differences were found in reported leisure constraints. Grade 3 and 7 girls more frequently reported fear of going out at night than boys. Grade 7 and 11 girls reported a lack of companions and too much schoolwork more often than boys. When examining the relationship between leisure constraints and reduction in physical activity levels, significance was found for distance in grade 3 and too much schoolwork for grade 11. However, physical activity levels were not affected indicating that participants appeared to be using negotiation strategies. Further research is needed to explore the constraints identified by these participants as they have important implications for their participation and leisure experiences. Use of an empirical measure of negotiation served as a useful tool for understanding leisure participation, as it provided a clear and accurate indication of levels of participation. When such measures are included along with opportunities to explore the context of negotiation strategies, a greater understanding of children's and adolescent's leisure will be obtained.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".