THE CONSTRUCTION STATE UNBOUND? Struggles over the Seoul Metropolitan Region’s Greenbelt in an Era of Planetary Urbanization
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".