Vulnerability to climate change hazards and risks: crop and flood insurance
Bibliographic record
Abstract
This paper reviews the widely used concepts of risk and vulnerability as they relate to climate and weather hazards, re‐conceptualizes these terms in the context of climate change and illustrates this development using crop and flood insurance as examples. Government subsidization of insurance against risks associated with adverse climatic conditions and weather events, such as flood damage and crop loss, may lead to individual decisions that actually increase the susceptibility of people, property and economic activities to those risks. The processes that give rise to this phenomenon are important in understanding the vulnerability of human populations to climate change. In many regions, existing conditions that give rise to flooding or crop failure are likely to be exacerbated by climate change over coming decades. In the climate change field, vulnerability has been conceptualised as a function of exposure to risk and as an ability to adapt to the effects. In this context, crop and flood insurance are possible adaptive measures. This treatment of vulnerability compares with similar concepts in insurance and risk management whereby events that cause loss are known as perils, and physical conditions, such as climate change, that increase the likelihood of a peril occurring, are known as physical hazards. Human behaviour that increases the exposure of individuals to potential perils is known as morale hazard or moral hazard, depending on the intentions of the person. Vulnerability consequently becomes a function of hazard and responses taken to reduce risk. Examples of crop and flood insurance programs from Canada, New Zealand and the U.S. are used to show how subsidized insurance might create a morale hazard in addition to physical hazards such as short‐term weather events and long‐term climate change, resulting in a higher level of vulnerability than would otherwise exist. These findings demonstrate that human behaviour affects the formation of both exposure and adaptive capacity in the context of vulnerability to climate change. Responses taken to increase adaptive capacity may in some cases be offset by individual behaviour that increases exposure.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".