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Record W2943004750 · doi:10.1017/s0144686x19000448

Critical evaluation of ‘ageing in place’ in redeveloped public rental housing estates in Hong Kong

2019· article· en· W2943004750 on OpenAlexfundno aff

Bibliographic record

VenueAgeing and Society · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsAutonomyScale (ratio)RentingGovernment (linguistics)BusinessPublic housingPopulation ageingService (business)PopulationPublic serviceEconomic growthPublic administrationEngineeringPolitical scienceMarketingGeographyEnvironmental healthMedicineCivil engineeringEconomics

Abstract

fetched live from OpenAlex

Abstract The tremendous growth in the ageing population over the past two decades has compelled the Hong Kong government to reformulate its housing policy by redeveloping and incorporating certain age-friendly housing design elements and facilities into the public housing schemes built in the post-war period. This research investigates whether these introduced design elements and facilities satisfy the numerous special needs of the seniors in line with the concept of ‘ageing in place’. Data were collected from 224 seniors through a comprehensive questionnaire survey in four large-scale redeveloped public rental housing estates. Using three designated built environment dimensions, namely micro, meso and macro, the results revealed that senior tenants were generally satisfied with the present living environments (in all the three scales) in the estates. At the micro-scale, seniors were satisfied with the level of privacy and sense of autonomy derived from the present design features in their homes. For the meso-scale, the study revealed that the seniors were particularly satisfied with the design elements such as convenient transportation and accessibility, including convenient walkways. At the macro-scale, the community care service is deemed important for seniors’ wellbeing. However, more attention is needed on safety measures in interior and shower areas, public seating in common areas and provision of sufficient community care services. This study provides insights for policy makers and development authorities on elderly housing provision.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.333
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2019
Admission routes1
Has abstractyes

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