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Towards guidelines for post‐disaster vulnerability reduction in informal settlements

2012· article· en· W1998983492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDisasters · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInformal settlementsHuman settlementVulnerability (computing)Settlement (finance)Disaster risk reductionEnvironmental planningNatural disasterDisaster researchNatural hazardGeographyBusinessEconomic growthComputer securityArchaeologyComputer scienceFinance

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.120
GPT teacher head0.392
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it