Physical Literacy in the Context of Climate Change: Is There a Need for Further Refinement of the Concept?
Bibliographic record
Abstract
The concept of physical literacy (PL) has witnessed enormous popularity in recent years and has undergone substantial theoretical evolvement during the last 2 decades. However, the research field pertaining to PL has not yet initiated discussions around the challenges of climate change and the alignment with conceptualizations of planetary health. Therefore, we argue that the consideration of an "ecological domain" for individual physical activity, in the form of ecological awareness, would further evolve the concept. We illustrate how to potentially integrate adjustments within the most frequent PL definitions of the field (eg, those in Australia, Canada, England, Ireland, the United States, or by the International Physical Literacy Association) without questioning the entire integrity of these elaborate conceptualizations. An ecological domain of PL would not only interact with the postulated physical, cognitive, psychological/affective, and social domains of PL but also have important implications for the (re)design of interventions and practices in physical activity contexts. We call the scientific community, both on national and international scales, to intensify the discussions and initiate a research agenda involving an "ecological domain" of PL.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".