Interpreting Cyclone Disasters in Bangladesh and Myanmar from Web-Based Newspaper Discourse: Media Framing of Cyclone Vulnerability on the Bay of Bengal Coast
Bibliographic record
Abstract
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...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".