MétaCan
Menu
Back to cohort
Record W4392659362 · doi:10.1080/13574809.2024.2325406

Language matters: types of informal built landscapes in global metropolitan regions

2024· article· en· W4392659362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Urban Design · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsToronto Metropolitan University
FundersHarvard University
KeywordsMetropolitan areaGeographyEconomic geographyCivil engineeringEnvironmental planningArchitectural engineeringEngineeringArchaeology

Abstract

fetched live from OpenAlex

This article analyses informal built landscapes in nine fast-growing global cities across diverse geo-political regions using historical maps, aerial photographs, and field visits. This empirical study investigates the urban form of informal built landscapes, identifying 10 main patterns of urban form in settlements created in the 1970–2020 period. This period was characterized by rapid spatial expansion of informal settlements. These trends raise the question of whether there were common characteristics of informal land occupation, how public sector interventions have changed informal settlements, and whether certain built landscapes were more prominent 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.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.032
GPT teacher head0.308
Teacher spread0.276 · 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