Over-the-Counter Weather Derivatives as a Snowfall Risk Management Tool for Municipalities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of weather derivatives to hedge against weather-related risks is a recent phenomenon, beginning in 1996 with firms in the energy industry. Although standardized weather contracts began trading on the Chicago Mercantile Exchange in 1999, they are of little value for many specialized applications in government and the private sector. The recent increase in the availability of weather contracts in the over-the-counter market, however, provides a wide range of tools for managing weather-related risks. Using snowfall data for a typical Canadian city, we show that weather derivatives can be effectively used to hedge the financial risks in snowfall removal expenditures. The debate regarding an accepted approach to pricing such contracts, however, remains a critical issue.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it