Financial impacts and risks of climate change: a case study of fish farming in the Mekong Delta, Vietnam
Bibliographic record
Abstract
Farmers face weather-related risks that are often overlooked in the literature. This paper analyses the potential impact of one weather-related risk, climate change. The context is aquaculture in the Mekong Delta of Vietnam, where severe storms are forecast to cause flooding and pond salination. In the Delta, the two principal farmed species are the Pangasius catfish and giant prawn; their cultivation provides employment to about a quarter of a million people, and they are a source of food security for more than a million people. This development engine could be jeopardised unless farmers are given sufficient lead-time to adapt to severe weather risks. An enterprise model is developed that conforms to existing bio-economic data for an average farm of the two principal species in the Mekong Delta. The model then simulates likely impacts of climate change on financial variables. It should be noted that these impacts are not definitive, but are merely 'guesstimates' and should be used with caution. However, they do provide an indication of likely trends. Strategies are suggested that might mitigate the negative effects of climate change.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".