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Record W4405713428 · doi:10.29173/hsi470

Natural disasters disproportionately affect populations and regions: A disaster analysis of the 2004 Indian Ocean tsunami

2022· article· en· W4405713428 on OpenAlex
Ella Korenvain

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHealth Science Inquiry · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsNatural disasterAffect (linguistics)Indian oceanGeographyOceanographyGeologyMeteorologyPsychology

Abstract

fetched live from OpenAlex

This paper is a comprehensive review of the 2004 Indian Ocean Tsunami that took place in Sumatra, Indonesia. The causes, as well as the direct and indirect impacts of this natural disaster are explored to understand the tsunami’s true damage and magnitude. A disaster risk analysis was conducted to provide an overview of the relationship between various interacting factors: the hazard, peoples’ exposure to the hazard, and their vulnerability to the hazard. This analysis is key in interpreting the risk of the hazard and determining its deadliness. Solutions and efforts to improve safety and resilience after the disaster are analyzed through several hazard paradigm lenses. The paradigms provide a well-rounded overview of the multifaceted nature of a hazard to better understand, plan, and mitigate associated risks. An overview of geographic areas and populations most at risk, as well as prospective solutions are described. Finally, this paper briefly discusses the growing impact of climate change on the frequency, risk, and magnitude of future extreme weather events.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0030.003
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.064
GPT teacher head0.390
Teacher spread0.326 · 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