The Role of Community Completeness in Older Adults Experiences of Health and Wellbeing: A Photovoice Study
Bibliographic record
Abstract
This thesis examines the role of community completeness in the health and wellbeing of older adults. Community completeness is a concept commonly used in urban planning policies by cities, however utilizations and definitions vary between locations. As the older adult population in Canada and around the world grows, it is important to understand older adults’ neighbourhood experiences, especially in a time of aging in place policy often encompassing concepts of community completeness. The main objectives of the study were to 1) explore the experiences of older adults within their neighbourhood in the context of their health and wellbeing, and 2) to create a complete community framework that can be used to promote health and wellbeing. A photovoice methodology was utilized to explore the neighborhood-based experiences of participants living in Edmonton, Alberta. These experiences were then examined using Amartya Sen’s capability perspective. The thesis begins by examining the academic literature on the associations between the built environment and health and wellbeing. In addition, planning policies from four Canadian cities are also examined. Four main pathways linking the built environment to health and wellbeing of older adults are identified: neighbourhood character, greenspace, walkability, and foodscapes. Utilizing the capability approach, various affordances were identified to propose a complete communities framework that is centered on health and wellbeing. These pathways include explorations of built environment components, as well as individual experiences such as happiness or fear which can influence health and wellbeing.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".