MétaCan
Menu
Back to cohort
Record W4413183599 · doi:10.1177/21582440251358108

Informing the Informal: Examining the Morphological Production of Informal Built Landscape Types

2025· article· en· W4413183599 on OpenAlexaff
Shelagh McCartney

Bibliographic record

VenueSAGE Open · 2025
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsToronto Metropolitan University
FundersDavid Rockefeller Center for Latin American Studies, Harvard UniversityWeatherhead Center for International Affairs, Harvard UniversityInternational Facility Management Association FoundationHarvard Graduate School of Design
KeywordsProduction (economics)Informal learningInformal settlementsSociologyGeographyEconomic growthEconomicsPedagogy

Abstract

fetched live from OpenAlex

Informal and formalized settlements present unique forms of informality that are significant for research on the urban development of cities in the Global South. This study adds to the body of research on informal settlements by adding methodological tools to analyze the implicit rules of informal urban areas from a typo-morphological perspective. To ground this research, this article examines the urban morphology of informal built landscapes in two large urban agglomerations: São Paulo and Manila. Ten cases have been identified, mapped, and analyzed to show their morphology in terms of street configuration patterns, service delivery, location in city structure, terrain, public space, access to plots, building typology, negotiation and organization of inhabitants, order of construction of buildings and streets, as well as control over buildings and plots. This paper focuses on a morphological discussion of informal urban patterns, providing a means for urban practice to encourage the creation of more just cities for the many urban settlers arriving in cities globally.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.005
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0000.000
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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueSAGE OpenSame topicUrban Design and Spatial AnalysisFrench-language works237,207