Mapping waterfront (re)developments in Southeast Asia: Speculation, entrepreneurial urbanism, and blue gentrification
Bibliographic record
Abstract
Waterfront (re)development projects have been prioritized by city officials around the world over the past several decades as a variety of public and private stakeholders increasingly compete for valuable coastal land. While academic research on waterfront redevelopments has expanded dramatically and examines the different motivations, types, stakeholders, and outcomes of these projects globally, English-language scholarship largely focuses on contexts in Europe and the anglosphere, with some attention paid to projects in China, Singapore, and a handful of other Global South cities. Despite the prominent coastal features of Southeast Asia and its fast pace of development, only limited scholarly attention has been paid to waterfront redevelopments in the region. In this paper, we identify waterfront developments launched over the past 15 years in 11 Southeast Asian countries. We point out several important trends in Southeast Asian waterfront developments fueled by massive waves of investment, including the increasing foreignization of urban space, which has resulted in speculative and entrepreneurial urbanism and blue gentrification, massive land reclamation, and limited public benefit. These patterns underscore the urgency of expanding urban research to account for the distinctive dynamics and implications of coastal urban transformation in Southeast Asia—not only in socio-economic and geopolitical terms, but also in light of the extreme ecological sensitivity of these coastal zones.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".