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Record W1992336044 · doi:10.1080/19376812.2014.943774

Affordable housing options for all in a context of developing capitalism: can housing transformations play a role in the Greater Accra Region, Ghana?

2014· article· en· W1992336044 on OpenAlexafffund
Louis Awanyo, Michelle McCarron, Emmanuel Morgan Attua

Bibliographic record

VenueAfrican Geographical Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversity of Regina
FundersUniversity of GhanaUniversity of Regina
KeywordsEconomicsCapitalismProduction (economics)Consumption (sociology)BusinessMarket economySociologyMacroeconomicsPoliticsPolitical science

Abstract

fetched live from OpenAlex

Sixty-one percent of households in the Greater Accra Region of Ghana (GAR), with an average size of 3.8 persons, occupy single bedrooms. Addressing their housing needs would require strategies of unleashing room supply through new housing and from existing housing through housing transformations (HT). Extant literature on HT in Ghana has generally focused on immediate empirical questions such as who are the housing transformers and their socio-economic identities and characteristics, and how to predict the occurrence of HT. Consumer sovereignty and utility maximization – the autonomous preferences of transformers – within the market context, as the determinant of the production and consumption of rooms, are implicit in these discussions, which are reminiscent of the ‘self-help’ housing thesis. This study’s alternative model employs primary data to identify the transformers and non-transformers as social classes with specific housing market capacities, and HT as enmeshed in broader processes of production and consumption of housing within the developing capitalist mode of production and its petty commodity production sector in GAR. The findings leave little optimism about a potential role of HT in making a significant dent in the staggering housing deficit.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.300
Teacher spread0.246 · 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 designQualitative
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

Citations17
Published2014
Admission routes2
Has abstractyes

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