Knowing and Understanding how to Manage One’s Physical Activity Practice: Contribution of Language, Thinking and Intelligence to Physical Literacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agreed upon components of physical literacy are (a) physical competence, (b) knowledge and understanding, (c) motivation and confidence, and (d) lifetime engagement. The purpose of this article is to discuss the development and use of the “knowledge and understanding” PL component in older students and adults with regard to the regulation of their health/fitness- and leisure-related physical-activity-practice (PAP). In a first section the author considers the pedagogical content knowledge (PCK) and the basic language that may be associated with the management of health- and fitness-oriented physical activities, differentiating elements that pertain to declarative, procedural or conditional knowledge. Based on exercise-monitoring procedures (E-MP) (essentially procedural knowledge) and on exercise-management rules (E-MR) (mostly conditional knowledge), the following section focuses on the development of PAP-management understanding and the related intelligence in its analytical, creative and practical dimensions. In a final section, the author explores briefly the matter of awareness and regulation in terms of exercise-management knowledge and understanding. Keywords: exercise-management awareness, exercise-management regulation, FITT formula, physical-activity monitoring
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it