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Record W1585882280

Using the British Household Panel Survey to explore changes in housing tenure in England

2007· article· en· W1585882280 on OpenAlexaboutno aff
Tom Sefton

Bibliographic record

VenueLondon School of Economics and Political Science Research Online (London School of Economics and Political Science) · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
FundersEconomic and Social Research CouncilLondon School of Economics and Political Science
KeywordsQuarter (Canadian coin)British Household Panel SurveyHousing tenureResidenceDemographic economicsUnemploymentPanel surveyLabour economicsWork (physics)EconomicsBusinessGeographyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Very little information exists about households' longer-term movements between tenures. Some cross-section datasets include information on length of stay in any residence but we have no systematic study of movement over time. This study uses the British Household Panel Study to examine movements by households over a ten-year period - 1994/5 and 2004/5. Changes in tenure are related to key life events - leaving home, marriage, having children, widowhood and retirement. The great majority of owner-occupiers remained in that tenure. This was somewhat less for those experiencing divorce or unemployment. Most public housing tenants remained in that tenure over the ten-year period especially the elderly and the unemployed or those outside the labour market. About a quarter moved into owner-occupation and half of those through the right to buy their dwelling. The analysis looks at the associations between moving into work and residential mobility, in particular the slower rate at which social tenants move back into employment.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.525
Threshold uncertainty score0.956

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.258
GPT teacher head0.415
Teacher spread0.157 · 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 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

Citations0
Published2007
Admission routes1
Has abstractyes

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Same venueLondon School of Economics and Political Science Research Online (London School of Economics and Political Science)Same topicUrban, Neighborhood, and Segregation StudiesFrench-language works237,207