Economic Analysis of Climate Change Adaptation Strategies in Selected Coastal Areas in Indonesia, Philippines and Vietnam
Bibliographic record
Abstract
Climate change with its attendant geophysical hazards is well studied. A great deal of attention has gone into analyzing climate change impacts as well as searching out possible mitigating adaptive strategies. These matters are very real concerns, especially for coastal communities. Such communities are often the most vulnerable to climate change, since their citizens frequently live in abject poverty and have limited capacity to adapt to geophysical hazards. Their situation is further complicated by the prospect of dealing with a confluence of hazards in comparison with those in other ecosystems. Against this backdrop Worldfish and the Economy and Environment Program for Southeast Asia (EEPSEA) collaborated to implement the cross-country study “Climate Change Impacts, Vulnerability Assessments, Economic and Policy Analysis of Adaptation Strategies in Selected Coastal Areas in Indonesia, Philippines, and Vietnam”. As its title suggests the study covered selected sites in Vietnam, Indonesia and the Philippines. Employing a gamut of interdisciplinary methodologies -- ranging from community-based approaches such as community hazard mapping and focus group discussions (FGDs) to regression techniques -- the study documented the impacts from three climate hazards affecting coastal communities. These were typhoon/flooding, coastal erosion, and saltwater intrusion. The team also analyzed planned adaptation options suited to implementation by communities and local governments, augmenting autonomous responses of households to protect and insure themselves from these hazards.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.013 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".