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Record W1994183577 · doi:10.1108/hcs-06-2013-0007

From Canada to Kircubbin: learning from America on housing an ageing population – part 2

2013· article· en· W1994183577 on OpenAlexaboutno aff
Eileen Thompson

Bibliographic record

VenueHousing Care and Support · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAusterityOriginalityPopulation ageingPopulationPublic housingPrivate sectorEconomic growthValue (mathematics)Public relationsBusinessPolitical scienceSociologyEconomicsSocial scienceQualitative research

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to learn lessons from North America on housing an ageing population, both in terms of supporting people to “age in place”, and available options for those who need/wish to move. The project, funded by the Winston Churchill Memorial Trust, comprised a six-week travel fellowship to USA and Canada to meet with housing professionals from the public and private sectors and find out about best practice initiatives and efficient models for housing older people. Design/methodology/approach – The paper is in two parts, of which this is the second. Part 2 focuses on the links between housing and health and, recognising significant differences between the countries, draws out lessons which may be applied as similar challenges of austerity, an ageing population and the increasing interest in personal budgets are faced. Findings – There is no one size fits all approach to addressing the housing needs of the older population; a continuum of options across tenures is required. There are opportunities for growth in the private and non-profit sectors in terms of the provision of services for the ageing population. Large scale social change comes from better cross-departmental coordination and cannot be achieved by the isolated intervention of a single organisation. Originality/value – This was a unique opportunity to learn lessons from North America on how to effectively meet the needs of the older population, now and in the future. The findings are based on the personal observations and conclusions of a housing practitioner.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.259
Teacher spread0.243 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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