A Physical Activity Practice Index for Older Students and Adults
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
This article puts forward a physical activity practice (PAP) index that could be used by older students (high school and college level) and adults who wish to monitor their PAP in order to regulate it. Authors explain the origin of the PAP index, identify PAP aspects such as frequency, duration, intensity and diversity as they relate to the index and describe the simple mechanics of its computation. Then, they discuss physical literacy (PL) awareness in terms of competence, knowledge and understanding, motivation toward PAP, and actual physical activity (PA) engagement. Regulation scenarios are presented in association with individuals’ PAP awareness. Finally, a few suggestions are added with regard to tailored PAP monitoring for more engaged physical literate persons. The PAP index described is intended to help individuals monitor their PAP over time, taking simultaneously into account its intensity and volume whatever the selected activity(ies). Willingness to monitor one’s PAP implies at least a minimal level of PL awareness. Besides reflecting on their PA-related knowledge and PA competency and capacities, individuals ought to understand their reasons for engaging into the regular practice of PA. Based on their answers to such questions, they can then engage into regulation scenarios with the help of monitoring instruments such as the one discussed in this article. Keywords: physical literacy, physical-literacy awareness, physical-activity-practice awareness, FITT formula, PAP monitoring
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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