Movement for movement: exercise as everybody's business?
Bibliographic record
Abstract
Exercise as medicine, is well established.1 However, the art of knowledge transfer and implementation of exercise/physical activity (PA) remains poorly embedded in society, strategy and clinical practice in all aspects of health.2 The reality of this situation is grim. Insufficient PA is 1 of the 10 leading risk factors for death worldwide, so exercise professionals and PA advocates have much work to do. The purpose of this editorial is to point towards a strategic plan which responds to the clear limitations of the current multiagency infrastructure for PA. We propose that this strategy should now consider how stakeholders can meet the calls of existing collaborative plans by working specifically as a community of practice3 (figure 1). Figure 1 A community of practice for exercise and physical activity (PA). Based on Wenger-Trayner and Wenger-Trayner.3 If the projected healthcare burden4 is realised, there will be no shortage of patients, in terms of healthcare ‘business’. Musculoskeletal problems and non-communicable diseases will dominate the landscape of tomorrow's patient care models.5 We will need all expert hands on deck to support …
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.016 | 0.023 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".