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Record W3196425904 · doi:10.1007/s13753-021-00365-3

Tourism Developments Increase Tsunami Disaster Risk in Pangandaran, West Java, Indonesia

2021· article· en· W3196425904 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueInternational Journal of Disaster Risk Science · 2021
Typearticle
Languageen
FieldEngineering
TopicEarthquake and Tsunami Effects
Canadian institutionsnot available
Fundersnot available
KeywordsTourismNatural hazardQuarter (Canadian coin)GeographyForensic engineeringEngineeringMeteorologyArchaeology

Abstract

fetched live from OpenAlex

Abstract On 17 July 2006, the tourist resort of Pangandaran on Java’s south coast was hit by a tsunami, resulting in 413 fatalities and severe damage to buildings. The tsunami resulted in major rebuilds with a focus on mass tourism. Assessments of the impact of a future tsunami focussed on building development and suggest limited change since 2006. This article presents a case study on the development of (largely domestic) tourism in Pangandaran and how this has increased the tsunami disaster risk. Tourist numbers were stable at about 900,000 visitors a year prior to the tsunami, down to slightly over 250,000 visitors a year in its aftermath, and from 2007 onwards numbers are doubling every three years to about 4 million visitors in 2019. The increase has been most pronounced during weekends. Prior to 2006, Pangandaran was characterized by wooden structures and one- and two-story buildings of clay-brick masonry; by 2019, 14 three to six-story hotels have been erected along the waterfront. With many more visitors, most of whom are unfamiliar with tsunami risks, and shelter facilities for less than a quarter of visitors during peak times, future impacts and the potential cost to life are considerably higher now than in 2006, especially if a tsunami were to hit over a weekend. All tourists upon arrival and throughout their stay should be better informed about the risks of tsunamis, and of the location of tsunami shelters and evacuation routes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.005
GPT teacher head0.229
Teacher spread0.225 · 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