Towards guidelines for post‐disaster vulnerability reduction in informal settlements
Bibliographic record
Abstract
Although the development community has long recognised that securing land tenure and improving housing design can benefit significantly informal settlement residents, there is little research on these issues in communities exposed to natural disasters and hazards. Informal settlements often are located on land left vacant because of inherent risks, such as floodplains, and there is a long history worldwide of disasters affecting informal settlements. This research tackles the following questions: how can informal settlement vulnerabilities be reduced in a post-disaster setting?; and what are the key issues to address in post-disaster reconstruction? The main purpose of the paper is to develop a set of initial guidelines for post-disaster risk reduction in informal settlements, stressing connections to tenure and housing/community design in the reconstruction process. The paper examines disaster and reconstruction responses in two disaster-affected regions-Jimani, Dominican Republic, and Vargas State, Venezuela-where informal settlements have been hit particularly hard.
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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 | 0.041 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".