Deconstructing Williamsburg: Using focus groups to examine residents' perceptions of the building of a walkable community
Bibliographic record
Abstract
BACKGROUND: Components of the built environment are associated with active living behaviors, but research in this area has employed surveys and other quantitative methods almost exclusively. Qualitative approaches can provide additional detail about how neighborhoods influence physical activity, including informing the extent to which such relationships are causal in nature. The purpose of this study was to gain an in-depth understanding of residents' attitudinal and behavioral responses to living in a neighborhood designed to be walkable. METHODS: Focus groups were conducted with residents of a planned retail and residential development that was designed to embody many attributes of walkability and was located within a large city in southwestern Ontario. In total, 31 participants provided qualitative data about neighborhood resources and dynamics, use of local services, physical activity behavior, and other related issues. The data were transcribed and coded for themes relevant to the study purpose. RESULTS: Salient themes that emerged emphasized the importance of land use diversity, safety, parks and trails, aesthetics, and a sense of community, with the latter theme cutting across all others. The data also revealed mechanisms that explain relationships between the built environment and behavior and how sidewalks in the neighborhood facilitated diverse health behaviors and outcomes. Finally, residents recited several examples of changes in behavior, both positive and negative, since moving to their current neighborhood. CONCLUSIONS: The results of this study confirmed and expanded upon current knowledge about built and social environment influences on physical activity and health. That many residents reported changes in their behaviors since moving to the neighborhood permitted tentative inferences about the causal impact of built and social environments. Future research should exploit diverse methods to more fully understand how neighborhood contexts influence active living.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".