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Record W2115931914 · doi:10.1177/1461444805058159

Policy Commentary

2005· article· en· W2115931914 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.

fundA Canadian funder is recorded on the work.
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

VenueNew Media & Society · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsWarning systemNatural disasterThe InternetHazardIndian oceanNatural hazardInternet privacyComputer securityBusinessComputer scienceGeographyTelecommunicationsMeteorologyWorld Wide WebGeologyOceanography

Abstract

fetched live from OpenAlex

The Indian Ocean tsunami of 26 December 2004 was one of the greatest natural disasters; it was also the first internet-mediated natural disaster. Despite the presumed ubiquity and power of advanced technologies including satellites and the internet, no advance warning was given to the affected coastal populations by their governments or others. This article examines the conditions for the supply of effective early warnings of disasters, drawing from the experience of both the 26 December 2004 tsunami and the false warnings issued after another great earthquake in the Sunda Trench on 28 March 2005. The potential of information and communication technologies for prompt communication of hazard detection and monitoring information and for effective dissemination of alert and warning messages is examined. The factors contributing to the absence of institutions necessary for the realization of that potential are explored.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.022
GPT teacher head0.314
Teacher spread0.292 · 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