The need for adolescents’ agency in salutogenic approaches shaping physical activity in schools
Bibliographic record
Abstract
Physical activity (PA) contributes to health throughout life. In particular, young people can benefit from this. Schools can play a key role in providing learning conditions to experience meaningful PAs aimed at inspiring students to lifelong PA. In this article, we argue the need for a salutogenic approach in schools focussing on respecting and enhancing adolescents' agency with regard to their PA. This approach entails listening to adolescents' perspectives and inviting them to participate in actively designing and carrying out PA as a prerequisite for their inclusive engagement. We unpack the concept of agency by drawing on insights from the Capability Approach. This provides input for the integration of agency in health promoting schools and salutogenic approaches, to enhance PA-related agency. Finally, we outline a research agenda to, eventually, create opportunities for students in schools to expand their PA-related agency. Lay Summary Physical activity (PA) contributes to health throughout life. Schools can play a key role in fostering meaningful PA experiences to inspire students to lifelong PA. This requires schools to focus on students' personal aspirations, providing them with the space to develop their autonomy and find opportunities to decide and act upon expanding their agency with respect to the physically active lifestyles they deem meaningful.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".