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 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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".