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Record W2101500010 · doi:10.69554/ynfr8429

Measuring disaster-resilient communities: A case study of coastal communities in Indonesia

2012· article· en· W2101500010 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

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsCanadian Red Cross Society
Fundersnot available
KeywordsVulnerability (computing)Community resilienceProcess (computing)Environmental resource managementResilience (materials science)Outcome (game theory)Index (typography)Disaster risk reductionSustainabilityProcess managementEnvironmental planningBusinessGeographyComputer scienceEnvironmental scienceResource (disambiguation)EconomicsComputer securityEcology

Abstract

fetched live from OpenAlex

Vulnerability reduction and resilience building of communities are central concepts in recent policy debates. Although there are fundamental linkages, and complementarities exist between the two concepts, recent policy and programming has focused more on the latter. It is assumed here that reducing underlying causes of vulnerabilities and their interactions with resilience elements is a prerequisite for obtaining resilience capabilities. An integrated approach, incorporating both the vulnerability and resilience considerations, has been taken while developing an index for measuring disaster-resilient communities. This study outlines a method for measuring community resilience capabilities using process and outcome indicators in 43 coastal communities in Indonesia. An index was developed using ten process and 25 outcome indicators, selected on the basis of the ten steps of the Integrated Community Based Risk Reduction (ICBRR) process, and key characteristics of disaster resilient communities were taken from various literatures. The overall index value of all 43 communities was 63, whereas the process and outcome indicator values were measured as 63 and 61.5 respectively. The core components of this index are process and outcome indicators. The tool has been developed with an assumption that both the process and outcome indicators are equally important in building disaster-resilient communities. The combination of both indicators is an impetus to quality change in the community. Process indicators are important for community understanding, ownership and the sustainability of the programme; whereas outcome indicators are important for the real achievements in terms of community empowerment and capacity development. The process of ICBRR approach varies by country and location as per the level of community awareness and organisational strategy. However, core elements such as the formation of community groups, mobilising those groups in risk assessment and planning should be present in all the countries or locations. As this study shows, community resiliency can be measured but any such measurement must be both location- and hazard-specific.

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 score0.481
Threshold uncertainty score0.796

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 communication0.0000.000
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 head0.094
GPT teacher head0.323
Teacher spread0.229 · 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

Quick stats

Citations71
Published2012
Admission routes1
Has abstractyes

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