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Record W2202484454 · doi:10.25336/p6s32x

The Housing Careers of Older Canadians: An Investigation Using Cycle 16 of the General Social Survey

2008· article· en· W2202484454 on OpenAlexaffvenue
Michael Haan, Thomas Perks

Bibliographic record

VenueCanadian Studies in Population · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of LethbridgeUniversity of Alberta
Fundersnot available
KeywordsHousing tenureGeneral Social SurveyLogistic regressionDemographic economicsExplanatory powerExplanatory modelSurvey data collectionEconomicsSociologyPsychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

In this paper we use the Aging and Social Support Survey (GSS16) and the theoretical conception of a ‘housing career’ to identify the correlates of housing tenure (rent vs. own) among Canadians age 45 and over. We draw on primarily US literature to isolate three general explanatory clusters (social support, health, and economic characteristics). Based on analyses using logistic regression, the results indicate that the majority of variation in housing tenure exists due to standard demographic and household characteristics. In fact, of the three focal explanatory clusters, only social support characteristics significantly enhance model fit beyond the baseline model, suggesting that the housing tenure of older Canadians hinges heavily on fairly standard characteristics.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.150
GPT teacher head0.355
Teacher spread0.205 · 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.

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

Citations7
Published2008
Admission routes2
Has abstractyes

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