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Record W1965594564 · doi:10.1108/09653561011052501

“The ripples changed our lives”: health in post‐tsunami Thailand

2010· article· en· W1965594564 on OpenAlexaff
Monir Moniruzzaman

Bibliographic record

VenueDisaster Prevention and Management An International Journal · 2010
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNatural disasterEthnographyMental healthOriginalityNarrativeParticipant observationSocioeconomicsGeographyQualitative researchMedicineSociologyPsychiatrySocial scienceArchaeology

Abstract

fetched live from OpenAlex

Purpose The December 2004 tsunami was one of the largest natural disasters in the recent history of Southeast Asia. This paper aims to unfold the experiences of tsunami victims in a highly affected region of Thailand and to examine their post‐tsunami health. Design/methodology/approach Ethnographic fieldwork was carried out in Khao Lak and Thi Muang, two major tsunami affected towns in southern Thailand in May 2007. Detailed informal interviews and participant observation were employed to obtain narratives of tsunami victims. Findings The research reveals that the health of the tsunami survivors has deteriorated, and that they are still experiencing psychological suffering two and a half years after the tsunami. Research limitations/implications The long‐term health condition and care should be prioritized in post‐disaster management. Originality/value This paper argues that inner healing, which is not usually considered a priority in the development discourse, is essential to relieve the mental pain of tsunami survivors and to aid their post‐disaster recovery. It highlights that culturally pertinent inner healing is invaluable.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.525

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 head0.047
GPT teacher head0.421
Teacher spread0.374 · 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 designObservational
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

Citations10
Published2010
Admission routes1
Has abstractyes

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