How Age Friendly is This City? Strategies for Assessing Age-Friendliness
Bibliographic record
Abstract
The Age-Friendly Cities framework, created by the World Health Organization (WHO), has emerged as a community-based response to the challenges of demographic aging and increasing urbanization. In 2010, London, Ontario, became the first city in Canada to join the WHO Global Network of Age-Friendly Communities. Network milestones require the measurement of the baseline age-friendliness of the community. The objectives of this thesis are: 1. Determine the best available assessment tools for measuring the age-friendliness of a community, and 2. Establish the baseline age-friendliness of London, Ontario. A scoping review was utilized to collect and assess available surveys and questionnaires. A quantitative survey of older adults in London was used to determine the baseline age-friendliness of the city and provide a template for other cities and communities. Findings indicate there is a paucity of tools available for AFC, and London is a moderately age-friendly city with specific areas for improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".