ENGAGING WITH MUNICIPAL PLANNERS WITH A DEMENTIA-INCLUSIVE PLANNING AND DESIGN GUIDE
Bibliographic record
Abstract
Abstract Dementia-friendly and inclusive community (DFC) action plans in British Columbian municipalities identify various planning and design strategies and actions to meet the goals of dementia-inclusivity. However, there is a lack of evidence-based design guidelines tailored to the context of British Columbia to support the implementation of these plans. To address this gap, a DFC planning and design guide was generated as part of the DemSCAPE study, consisting of planning and design principles and guidelines for wayfinding, safety, social interaction and access to amenities for people living with dementia. A series of knowledge mobilization (KM) activities will explore and augment the relevance, uptake, and implementation of this guide. Two focus groups (60-90 min; N = 5-7 per session) were conducted with municipal professionals working in two municipalities (i.e., City of Burnaby and City of Richmond) in Metro Vancouver. The existing municipal action plans emphasize the need for collaboration and dialogue across different departments of local government, e.g., social planners and seniors services coordinators (staff who are more closely connected with and help coordinate these plans) and planners, designers, and engineers. The focus groups are intended to trigger inter-departmental dialogue centered on DFC planning and design and examine DFC strategies and actions from various stakeholders’ perspectives within the scope of municipal planning. This KM project is expected to make meaningful contributions to the DFC initiatives of local government in BC by providing guidelines to municipal planners on how to apply a dementia-friendly and inclusive lens in planning and design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".