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Record W4414292341 · doi:10.1111/1468-2427.70018

THE CONSTRUCTION STATE UNBOUND? Struggles over the Seoul Metropolitan Region’s Greenbelt in an Era of Planetary Urbanization

2025· article· en· W4414292341 on OpenAlexfundno aff
Laam Hae, Jamie Doucette

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaAcademy of Korean StudiesYork UniversityKorean Studies Promotion Service
KeywordsUrbanizationMetropolitan areaSituatedPoliticsState (computer science)AllianceUrbanism

Abstract

fetched live from OpenAlex

Abstract This article builds on recent interventions into the study of planetary urbanization that call for greater interaction with the multiple social struggles and standpoints that embed this process. To do so, we advocate for academic engagement between planetary urbanization and the concept of the ‘construction state’. This is a term used in Japan and South Korea to describe an alliance between development corporations and the state, one whose expansionary logic accords with the notions of planetary and extended urbanization and acts as a co‐constitutive, regional driver of it. To better situate this concept, and to highlight the social struggles that inform it, we examine the politics of greenbelt deregulation and the expanding real estate‐led urbanization in the Seoul Metropolitan Region in recent decades. We show how the construction state and its supply‐centrism played a key part in the ‘explosive’ process of greenbelt development and examine the dynamics of the struggles that activists waged against it. By doing so, we contribute to ongoing debates about planetary urbanization as an open totality of processes, stress the importance of a situated approach that foregrounds the diverse practices and struggles that shape it and encourage communication between critical standpoints.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.689

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 science0.0010.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.389
Teacher spread0.340 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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