Using willingness‐to‐pay to assess the economic value of weather forecasts for multiple commercial sectors
Bibliographic record
Abstract
Abstract This paper uses an alternative to the usual cost‐avoidance approach to estimating the value of weather forecast products. Value is estimated via a demand‐based approach based on the willingness to pay of those who use weather forecast services. Contingent valuation is used to estimate the benefits generated by an automated telephone‐answering device that provides weather forecast information to commercial users in the Toronto area of Ontario, Canada. Commercial sectors included in the study are construction, landscaping/snow‐removal businesses, TV and film, recreation and sports, agriculture, hotel and catering, and institutions such as schools and hospitals. Average value per call varied by commercial sector, from $2.17 for agricultural users to $0.60 per call for institutional users, with an overall mean of $1.20 per call. At roughly 13,750,000 commercial calls annually, this would result in an estimate of benefits generated by the service to commercial users of $16,500,000 per year. Copyright © 2003 Royal Meteorological Society
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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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".