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Interpreting Cyclone Disasters in Bangladesh and Myanmar from Web-Based Newspaper Discourse: Media Framing of Cyclone Vulnerability on the Bay of Bengal Coast

2011· article· en· W2613300282 on OpenAlex
Harun Rashid

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueArab world geographer · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNewspaperFraming (construction)BENGALBayCyclone (programming language)GeographyPopulationSociologyMedia studiesEngineering

Abstract

fetched live from OpenAlex

Based on discourse analysis of 226 Web-based newspaper reports on three major cyclones in the Bay of Bengal—Gorky (1991), Sidr (2007), and Nargis (2008)—this study assesses a number of research assumptions dealing with media framing of cyclone vulnerability on the Bay of Bengal coast. Using a social constructionist perspective, the content of each report is classified into several segments, each providing data on how the selected newspapers framed certain aspects of the disaster news. Frequency counts of these themes provide specific data for assessing several research paradigms. Newspaper discourse was replete with references to a set of socio-economic variables as elements of risk, such as an impoverished population, marginal locations in low-lying topographic settings, poor-quality housing, and a risk-prone subsistence economy, as the context for cyclone vulnerability on the Bay of Bengal coast. Data obtained from discourse analysis also provide evidence of cyclone victims' vulnerability due to logisti...

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 score0.107
Threshold uncertainty score1.000

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 studies0.0000.001
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 head0.017
GPT teacher head0.263
Teacher spread0.246 · 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