MétaCan
Menu
Back to cohort

Writing the Lines of Connection: Unveiling the Strange Language of Urbanization

2008· article· en· W2040031318 on OpenAlexaff
Nathalie Boucher, Mariana Cavalcanti, Stefan Kipfer, Edgar Pieterse, Vyjayanthi Rao, Nasra Smith

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsYork UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsHumanitiesUrbanismArticulation (sociology)SociologyUrban cultureGeographyPolitical scienceArtArchitectureArchaeologyLaw

Abstract

fetched live from OpenAlex

Abstract Across urban studies there is an increasing preoccupation with the forms of articulation that link a multiplicity of cities across a region often known as the ‘Global South’. How do cities such as Jakarta, São Paolo, Dakar, Lagos, Mumbai, Hanoi, Beirut, Dubai, Karachi, for example, take note of each other and engage in various transactions with each other in ways that are only weakly mediated by the currently predominant notions of urbanism? What might be the lines of connection and how do different cities recognize and experience the textures of their different histories and characters? Six urbanists are assembled here to write in conversation with each other as a way to embody possible collaborative lines of inquiring about these issues. Résumé Dans la recherche urbaine, se dessine une préoccupation croissante pour les formes d'articulation qui relient une multiplicité de grandes villes dans une région souvent identifiée comme ‘les pays du Sud’. Comment des villes comme Jakarta, São Paolo, Dakar, Lagos, Mumbai, Hanoï, Beyrouth, Dubaï, Karachi, s'intéressent‐elles les unes aux autres et se livrent‐elles à des transactions mutuelles selon des modalités qui ne passent que très rarement par les grandes notions actuelles d'urbanisme? Quelles pourraient être les voies de raccordement et de quelle manière des villes différentes reconnaissent‐elles et appliquent‐elles les contextures diverses nées de leur histoire et de leurs caractères? Six urbanistes se sont réunis pour rendre compte de leur discussion commune de manière à concrétiser des axes possibles d'études en collaboration concernant ces questions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.262
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.128
GPT teacher head0.410
Teacher spread0.282 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Urban and Regional ResearchSame topicUrban Planning and GovernanceFrench-language works237,207