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Record W4281606952 · doi:10.1002/psp.2593

Living alone in the age of freedom: The paradox of solo households in postapartheid South Africa

2022· article· en· W4281606952 on OpenAlexaff
Dorrit Posel, Mark Hunter

Bibliographic record

VenuePopulation Space and Place · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsPovertyUrbanizationQualitative propertyDemographic economicsInequalityWork (physics)State (computer science)GeographyGender studiesSociologySocioeconomicsEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Abstract This paper considers an apparent paradox in South Africa: the share of single‐person households increased after the end of apartheid despite the ending of apartheid's racial laws that restricted ‘African’ families from living together, the postapartheid state's building of around four‐million low‐cost houses for families, the economies of scale offered by multiple‐person households in a country where poverty remains prevalent and the reduced significance of some of the longstanding sites of single‐person households—including mining compounds and hostels for men. Bringing together quantitative and qualitative data, we argue that solo dwelling remains associated with persistent rural–urban spatial divisions, increased migration and urbanization, continued declining marriage rates and the nature of employment. These arguments are supported by quantitative data that show an increase in solo dwelling, its greater occurrence among men and working‐age African men, in particular, its concentration in certain urban spaces and the way it fluctuated in the 2000s according to changing labour market conditions. We also draw on a township survey and interviews that show how, as apartheid restrictions collapsed, new areas of land suitable for solo living became available in the 1990s and provide examples of unmarried and married adults living alone, including to access work opportunities.

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)0.000
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 score0.425
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.048
GPT teacher head0.264
Teacher spread0.216 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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