How Development Affects News Media Coverage of Earthquakes: Implications for Disaster Risk Reduction in Observing Communities
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.
Bibliographic record
Abstract
Previous research suggests that lesson-drawing news coverage of disasters can create windows of opportunity for policy learning in the observing communities. This is especially important for cities facing similar vulnerabilities to disaster-affected communities, where they can learn from their events to pursue disaster risk reduction policies to mitigate against those risks at home. However, little is known about the conditions under which newspapers in at-risk communities provide the type of news coverage necessary for policy learning. Using logistic regression to analyze an original dataset produced from a content analysis of five newspapers’ coverage of five earthquakes, we demonstrate that the level of development of the disaster-stricken community systematically influences the nature of news coverage in at-risk communities. These results have important implications for the understanding of urban disaster risk reduction, suggesting that the conditions for bottom-up policy learning are more likely to occur following disasters in wealthier countries.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it