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Record W2124806403 · doi:10.5334/sta.ap

The Urban Crisis in Sub-Saharan Africa: A Threat to Human Security and Sustainable Development

2013· article· en· W2124806403 on OpenAlexvenueno aff
Mediel Hove, Emmaculate Tsitsi Ngwerume, Cyprian Muchemwa

Bibliographic record

VenueStability International Journal of Security and Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationSanitationPaceDevelopment economicsSustainable developmentEnvironmental planningNatural resource economicsBusinessEconomic growthGeographyEconomicsPolitical scienceEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Urban centres have existed and have been evolving for many centuries across the world. However, the accelerated growth of urbanisation is a relatively recent phenomenon. The enormous size of urban populations and more significantly, the rapidity with which urban areas have been and are growing in many developing countries have severe social, economic and physical repercussions. This paper argues that the accelerated growth of urbanisation has amplified the demand for key services. However, the provision of shelter and basic services such as water and sanitation, education, public health, employment and transport has not kept pace with this increasing demand. Furthermore, accelerated and poorly managed urbanisation has resulted in various types of atmospheric, land and water pollution thereby jeopardising human security. This paper offers the conclusion that the increased environmental, social and economic problems associated with rapid urbanisation pose a threat to sustainable development, human security and, crucially, peace.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.278
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations211
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueStability International Journal of Security and DevelopmentSame topicUrban and Rural Development ChallengesFrench-language works237,207