Time to walk the talk: embracing the built environment to promote physical mobility
Bibliographic record
Abstract
In Outliers, Malcolm Gladwell argued that ‘success’—whether it be sporting, financial or health-related—resulted not from genetic mutation but from an environment that provides some substantial advantage.1 In this Warm up, we draw attention to the Built Environment as an overlooked determinant of health.2,–,4 Remember, the built environment—the places in which people live, work and play—is the setting for your patients to execute your activity prescription! People who rely only on ‘recreational or leisure time’ to battle the epidemic of physical inactivity usually lose. Time to recreate is constrained by many factors including increasing time required to travel and work.5 On the other hand, those who walk to the bus or train, who walk to shops in their local community and who bike to work are likely to meet physical activity guidelines.6 7 A built environment that supports walking, biking and transit over driving can help to structure daily patterns to include regular physical activity. A transit trip is an interrupted walk trip—one study found that, …
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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 | 0.003 | 0.004 |
| 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 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".