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Record W1626195261 · doi:10.1108/ijdrbe-09-2013-0039

Role of social resilience in mitigating disasters

2015· article· en· W1626195261 on OpenAlexaffabout
N. Nirupama, T. Popper, A. Quirke

Bibliographic record

VenueInternational Journal of Disaster Resilience in the Built Environment · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsYork University
Fundersnot available
KeywordsDisaster risk reductionResilience (materials science)Government (linguistics)Corporate governancePopulationOriginalityEmergency managementEnvironmental resource managementEnvironmental planningPolitical scienceBusinessGeographySociologyEconomicsSocial scienceFinanceQualitative research

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to analyze a few recent earthquakes, gain insights into the role of social resilience in the severity of disaster impact and offer plausible approaches to mitigate future disaster impact. Managing and alleviating social and psychological harm among people, in the face of recurring disasters in the world, is very important. Design/methodology/approach – An approach of event comparison has been adopted in this paper. Three recent earthquake events, the 2012 event in Haida Gwaii, Canada, the 2010 event in Christchurch, New Zealand, and the 2011 Japan earthquake and tsunami have been examined through the lens of social resilience of affected population. Findings – Japanese people illustrated patience, tolerance and consideration for other impacted people, proving that it is an effective and efficient approach to dealing with a disaster. New Zealand’s resilience can be attributed to having a governance that is well aware of the hazards in the country. In Canada, however, as of 2001, there are barely any government-funded programs geared toward seismic risks research. Although economically, politically and technologically similar countries can easily learn from this review on resilience, it is important to recognize that there are limitations. Originality/value – The research provides a unique point of view into three different cases of earthquake occurred recently in developed economies. The analysis presented in the paper focuses on social resilience, governance and people’s reaction to the disaster which is vital for disaster risk reduction strategies and programs development as well as implementation.

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.

How this classification was reachedexpand

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.021
GPT teacher head0.306
Teacher spread0.285 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2015
Admission routes2
Has abstractyes

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