Principles for climate-related resettlement of informal settlements in less developed nations: a review of resettlement literature and institutional guidelines
Bibliographic record
Abstract
The severity of climatic changes threatening urban coastal areas is introducing and intensifying environmental hazards that are endangering physical safety and livelihood security. This paper considers retreat, one of three broad adaptation options proposed by the Intergovernmental Panel on Climate Change, as a possible climate change adaptation strategy for low-income communities in less developed nations. Resettlement as climate change adaptation is a developing concept, with minimal guidelines and academic literature on the topic. Thus, this review expands beyond climate change, considering three literature themes surrounding resettlement: (1) climate change, (2) hazard and natural disasters (i.e. floods, hurricanes, and earthquakes), and (3) economic development (i.e. dam construction and natural resource extraction). The review extracts successful resettlement planning and approaches, as well as the lessons learned, to identify five principles for resettlement in a climate change context: Proactivity, Communication and Participation, Permanence, Compensation, and Livelihood Protection. The results of the analysis suggest five principles that can be used as a guideline for implementing resettlement as climate change adaptation for low-income and informal communities in less developed nations. Ultimately, these recommendations can be used to assess the appropriateness and feasibility of employing resettlement as managed retreat in less developed nations.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".