Assessing the impact of tropical cyclones on economic sectors in Costa Rica, Central America
Bibliographic record
Abstract
Tropical cyclones (TC) pose a persistent natural hazard to Costa Rica. Exposure to natural hazards, such as mass movements and floods, is compounded by a growing urban population and inadequate land use planning. This study conducted a comprehensive analysis of the economic impacts of TC of Costa Rica from Hurricane Joan in 1988 to Hurricane Eta in 2020, assessing the impact by municipality and economic sector using baseline information of the Ministry of National Planning and Economic Policy. According to the study, road infrastructure (933.8 US million), agriculture (280.5 US million), river rehabilitation (153.96 US million), housing 98.26 (US million), and health (81.74 US million) were among the sectors most severely affected by TC over the past 30 years. The Pacific basin municipalities in Costa Rica were found to be the most vulnerable, primarily due to the indirect impacts of TC. The study's results offer useful information on the economic sectors and municipalities that are most exposed from TC in Costa Rica and provide a replicable methodology for other regions and countries facing similar tropical phenomena.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".