Urban climate governance in Southeast Asian small and mid-sized cities: undermining resilience and distributing risks unevenly
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.
Bibliographic record
Abstract
Secondary cities are home to most of the world's urban populations vulnerable to climate change, yet researchers and policymakers have devoted less attention to them than large and megacities. To help address this gap, this paper explores the relationship between incomplete decentralized governance, climate change, and urban resilience. It does through the case studies of secondary cities of Cambodia, Myanmar, Thailand, and Vietnam. Secondary cities are of importance because they are the fastest growing cities in the Global South but also because they have weaker capacity to address climate risks. Through these case studies, the paper draws comparisons between the different cases to look at the linkages between decentralization and urban resilience in secondary cities. Overall, it argues that climate governance, due to the retention of power and resources by central bureaucrats along with fragmented governance structures, and misaligned incentive structures which prioritize economic growth over climate protection have undermined resilience building and contributed to the uneven distribution of climate risks in these cities.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it