Urban Water Management and Governance in Southeast Asian Cities
Bibliographic record
Abstract
Abstract Scholarship on the topic of urban water management in Southeast Asian cities, both contemporary and historical, centers on issues of contested control over water, reliance on infrastructure, and governance of populations. Such work offers insights regarding the enactment of power relations in Southeast Asian cities, particularly via infrastructure, and how this has played out with myriad effects across the region. To approach the study of water management in cities in the region is to simultaneously inquire into topics of fragmentation, informality, climate change, urban ecologies, and sanitation. Across this varied work is a concern for the ways that water infrastructure developments and failures have shaped the ways that Southeast Asian cities provide, or deny, access to the most vulnerable. The resulting unevenness and fragmentation have meant that water management and infrastructure have been sites of struggle. Examination of this scholarship highlights new insights into power and water across work by anthropologists, historians, geographers, political ecologists, and development studies scholars. In this literature, there are broader conceptual and practical shifts in focus that move from an emphasis on water management as control, to the emergence of governance of not only water but also the control of populations and urban space as a key concern and the “internal” politics of the governed. In other words, attempts to control water create and shape access and exclusion to urban water and therefore play a role in struggles and contestations over power in Southeast Asian cities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".