Economic Impacts of the 2011 Tohoku‐Oki Earthquake and Tsunami
Bibliographic record
Abstract
This paper provides an overview of economic impacts in the first year after the 2011 Tohoku‐oki earthquake, tsunami, and nuclear accident—at an estimated ¥16.9 trillion (US$211 billion) in direct damage, the costliest natural disaster on record. Documented costs to date include ¥2.9 trillion in insurance payouts and ¥17.7 trillion in response and recovery budgets by the national government that will be financed largely by tax increases and bonds. In the regions with physical damage, fisheries and agriculture, among other sectors, were very hard hit. The disaster also caused measurable economic impacts well beyond the damage regions, including losses in gross domestic product (GDP), in manufacturing from supply‐chain disruptions, and in retail trade and tourism due to restrained consumption and radiation fears. Reduced capacity for generating electricity has led to substantial energy conservation nationwide. Results from applying a loss estimation model demonstrated good agreement with observed post‐disaster economic activity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".