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Record W2124957274 · doi:10.1080/00420980020080271

Ruralopolises : The Spatial Organisation and Residential Land Economy of High-density Rural Regions in South Asia

2000· article· en· W2124957274 on OpenAlexaff
Mohammad A. Qadeer

Bibliographic record

VenueUrban Studies · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsQueen's University
Fundersnot available
KeywordsMetropolitan areaGeographyUrbanizationEconomic geographyFrontierSettlement (finance)PopulationRural areaLand useAgrarian societyRural settlementHuman settlementEconomic growthEconomyRegional scienceAgriculturePolitical scienceEconomicsSociologyArchaeology

Abstract

fetched live from OpenAlex

Many rural regions, extending over thousands of square kilometres, in parts of Asia and Africa, have population densities comparable to Western metropolitan areas. In these agrarian and poor regions, population density is precipitating thresholds for collective facilities and services on the one hand, and squeezing the provision of land for living on the other. Such regions have been named ruralopolises to underline the fusion of rural economic and social systems with metropolitan spatial organisations. Ruralopolises are the sites of urbanisation through implosion. This paper outlines the phenomenon of ruralopolises and explores their emerging forms of settlement and evolving residential land tenures. It is essentially a conceptual exploration of high-density rural settlement systems based upon examples and observations from south Asian ruralopolitan regions. Given the scale of ruralopolitan regions in the Third World, it appears that ruralopolises are another urban frontier ripening for spatial and infrastructural crises in the 21st century.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
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 head0.028
GPT teacher head0.264
Teacher spread0.235 · 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

Citations70
Published2000
Admission routes1
Has abstractyes

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