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Record W3136290802 · doi:10.1177/0975425321997973

Urban Sprawl and Land Cover in Post-apartheid Johannesburg and the Gauteng City-Region, 1990–2018

2021· article· en· W3136290802 on OpenAlexaff
Samy Katumba, David Everatt

Bibliographic record

VenueEnvironment and Urbanization Asia · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsUrban sprawlUrbanizationGeographyContext (archaeology)Economic growthPopulationEconomic geographyPoliticsPopulation growthUrban planningPolitical scienceDevelopment economicsEnvironmental planningSociologyEconomicsArchaeologyCivil engineering

Abstract

fetched live from OpenAlex

Johannesburg and the broader Gauteng City-Region in which it is located are considered to be the economic powerhouse of South Africa. This has led to massive population growth in the region, as well as severe inequality. Given South Africa’s history of racially excluding black South Africans from urban areas, ongoing research in this area has to analyse land cover and define ‘sprawl’ in a context where the technical language has politically loaded overtones. This article tries to understand the scale of informality within a broader examination of urbanization and sprawl. It concludes that in the absence of a formally adopted urban edge and under massive pressure from population growth (natural and via migration), formal dwellings (residential and economic) have grown unchecked, and informality is now growing at high speed and also largely without regulation or control. With no apparent political will to stop urban sprawl, both informal and formal covers are steadily pushing towards provincial borders, while densifying in Johannesburg in particular.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.821

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.166
Teacher spread0.160 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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