Alternatives to Long Distance Resettlement for Urban Informal Settlements Affected By Disaster and Climate Change
Bibliographic record
Abstract
Planned or managed resettlement is increasingly being seen as a logical and legitimate disaster risk reduction and climate change adaptation strategy for urban informal settlements in many developing country cities. Our understanding of the 50+ year history of “Development-induced Displacement” (i.e. resettlement for resource extraction or development project purposes) strongly suggests that resettlement, particularly long distance resettlement, often triggers significant, negative impacts for resettled communities. We now understand that long distance resettlement should be seen as an option of last resort. Under most climate change scenarios, informal settlements in coastal, or riverside locations are expected to be impacted negatively by climatic change, and thus the question of whether or not to resettle (despite the negatives associated with this) still arises. This paper will present several emerging and innovative alternatives to long distance resettlement, including the so-called “vertical resettlement”, amphibious and floating housing, “near-site” resettlement, and in-situ climate change adaptation/upgrading. These alternatives collectively allow for a local “re-imagining of informal settlements” rather than simply “resettlement”. The research methods used in this paper include a review of secondary data (n=20), and limited primary field research involving resettlement site observation and several key informant interviews (n=2).
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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 | 0.001 | 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 | 0.000 |
| 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 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".