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Record W4404094525 · doi:10.1080/02697459.2024.2425249

Perspectives of municipal professionals on adopting a dementia-friendly and inclusive approach in urban planning and design in British Columbia, Canada

2024· article· en· W4404094525 on OpenAlexafffundabout
Kishore Seetharaman, Habib Chaudhury, Atiya Mahmood, Alison Phinney, Richard Ward

Bibliographic record

VenuePlanning Practice and Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
FundersAlzheimer Society
KeywordsDementiaUrban planningEnvironmental planningTown planningUrban designPublic administrationPolitical scienceSociologyCivil engineeringEngineeringGeographyMedicine

Abstract

fetched live from OpenAlex

An accessible and navigable neighbourhood physical environment is a critical part of dementia-friendly and inclusive communities (DFCs). Municipalities in British Columbia (B.C.), Canada have committed to the vision of DFCs with action plans outlining priorities in planning, design, engineering, and services. City planners and designers play an instrumental role in implementing these plans. Our study aims to understand their needs and challenges in implementing dementia-inclusive planning and design. Semi-structured interviews were conducted with 16 planners and designers in Metro Vancouver, B.C. Findings reflect two broad themes: 1) augmenting DFC-related knowledge and awareness and 2) integrating DFC approach in general 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0360.010
Scholarly communication0.0090.001
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.098
GPT teacher head0.473
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes3
Has abstractyes

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