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Record W3133427476 · doi:10.1080/26892618.2021.1877861

Exploring Stakeholder Perspectives on the UK’s Regulatory Tools for Accessible Housing: Lessons for Canada

2021· article· en· W3133427476 on OpenAlexaffabout
Katie Vaughan, Mikiko Terashima, Kate Clark, Katherine Deturbide

Bibliographic record

VenueJournal of Aging and Environment · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsDalhousie University
Fundersnot available
KeywordsStakeholderStock (firearms)BusinessKey (lock)Public relationsPolitical scienceEconomic growthPublic administrationEngineeringEconomicsComputer science

Abstract

fetched live from OpenAlex

Accessible housing is an urgent issue for countries experiencing rapid population aging. For over 20 years the United Kingdom’s (UK) building code (Part M) and Lifetime Homes Standard have been researched as leading practices to increase accessible housing stock and allow older adults to stay in their communities. This review compiles key stakeholder groups’ perspectives on these regulatory tools. Five main themes and ‘lessons learned’ were derived to anticipate potential challenges and inform proactive response for planners and policy makers in Canada and other countries when developing their own accessible housing regulation.

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)0.024
metaresearch head score (Gemma)0.029
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: none
Teacher disagreement score0.121
Threshold uncertainty score0.880

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0260.008
Scholarly communication0.0140.005
Open science0.0020.007
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.424
GPT teacher head0.358
Teacher spread0.066 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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