Associations between the built environment, total, recreational, and transit-related physical activity
Bibliographic record
Abstract
BACKGROUND: Many aspects of the built, physical environment have been shown to be associated with physical activity, but little research has focused on the unique circumstances and urban form of the suburban environment. The following analyses explore the associations between features of the built environment and components of overall physical activity, after accounting for neighborhood variability using hierarchical linear modeling. METHODS: These analyses utilized regionally-specific Geographic Information Systems data along with health measures collected from the 2007-8 Canadian Community Health Survey. Linear and logistic regression models explored the associations between measures of the built environment with leisure-time and transport-related physical activity. RESULTS: Respondents living with the highest number of intersections were more likely to engage in walking or cycling for leisure (OR: 1.85 CI 95%: 1.23-2.78), and in general, those living in areas with higher residential density were more likely to engage in active modes of transportation (OR: 2.67, CI 95%: 1.34-5.34). CONCLUSIONS: Further analyses are necessary to clarify the extent to which modifications to such features of the built environment may improve physical activity participation in similar suburban communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".