Implementing Dementia-Friendly Land Use Planning: An Evaluation of Current Literature and Financial Implications for Greenfield Development in Suburban Canada
Bibliographic record
Abstract
The number of people with dementia worldwide will reach 115.4 million by 2050. This accelerating crisis has sparked research on how to design neighbourhoods for those with early dementia, and how to empower them through built environment changes to remain in their community for as long as possible. There are numerous benefits for persons with dementia who continue access to their neighbourhood: physical activity, sense of dignity, social interaction, autonomy and psychological wellbeing. In this paper, I examine 17 recommendations (urban design and land use strategies) identified as ‘dementia-friendly’, within dementia design and planning literature. Each is then examined against the planning frameworks for a mid-size suburban municipality in Ontario and assessed for its financial impact on a base case subdivision using pro forma analysis. The effect on the financial return for a developer was minimal, demonstrating that establishing these recommendations as policy is viable, through regulation and incentives.
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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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".