Comparing perceived and objective measures of neighbourhood built environments among youth and adults in Canada
Bibliographic record
Abstract
OBJECTIVES: To compare perceived and objective measures of the neighbourhood built environment among a representative sample of youth and adults in Canada. STUDY DESIGN: Cross-sectional study. METHODS: Two cycles (N = 7948) of the Canadian Health Measures Survey (2016-19) were linked to objectively-measured built environment data. Objective measures included walkability, cycling paths, recreation facilities, trails, and major roadways. Perceived built environment features were used to derive a composite measure of walkability. Perceived and objective measures were compared using age group- (12-17, 18-64, 65-79 years) and sex-stratified chi-square tests, Pearson correlations, and independent t-tests. RESULTS: Although objective measures did not differ by age, youth and working-aged adults generally perceived more neighbourhood amenities than older adults. Adults were more likely than youth to report poorly maintained sidewalks and traffic as barriers to walking and cycling. No sex differences were observed. Across all age groups, the perceived presence of dense housing, shops, transit stops, sidewalks, cycling infrastructure, and low-cost recreation facilities increased with objectively-measured neighbourhood walkability. Perceived and objectively-measured walkability were moderately correlated; features such as transit, sidewalks, recreation facilities, and cycle paths were more common in neighbourhoods where residents reported perceiving them. CONCLUSIONS: Age differences in perceived environmental supports and barriers highlight the need to address age-related disparities to improve walkability. Future research should consider the relationship between perceived and objective built environment features and their impact on physical activity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".