Histories of Urban Deltascapes: A Comparison of Arles and Kolkata
Bibliographic record
Abstract
Abstract Delta cities are exposed to cycles of fluvial risks that have been managed across space and time. Floods and flood mitigation in urban deltascapes are therefore dependent on territorial and historicised dynamics. This paper uses historical urban political ecology (HUPE) to unravel the changing interactions between biophysical and political-economic processes affecting urban deltascapes in particular periods from the sixteenth century onwards. We present two case studies: Arles (on the Rhône Delta, France) and Kolkata (on the Bengal Delta, India). Our empirical findings point to the influence of connected global processes and to similarities in historical trajectories. In particular, both case studies reveal state efforts to 'fix' the fluid deltascape originally managed by local institutions, altered flood vulnerabilities (in terms of frequency, intensity and space), and more recent initiatives of mediation between interest groups. Through this unexpected comparison, more generally, we aim to contribute to a (global) environmental history that is sensitive both to local specificities and complexities and to the influence of global processes.
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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".