Assessment of the benefits of the Chinese Public Weather Service
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
ABSTRACT The present study aims to understand the public opinion on the Chinese Public Weather Service and evaluate its benefits. Statistics based on a nationwide survey conducted in China in 2006 show that the receipt and perception of weather information vary across different ages and groups. People obtain weather information from various sources (television ranks first); younger generations favour new media. There is a high demand for information services related to severe weather and short‐range weather, which have the largest impact on daily lives and professional needs. The respondents' satisfaction with the current weather service and forecast accuracy are very high, although the accuracy of weather forecasts requires improvements. The benefits of the Chinese Public Weather Service and cost–benefit ratios are evaluated via direct, indirect and reverse willingness‐to‐pay evaluation models. For the entire country, the benefit of the Chinese Public Weather Service is estimated to be at least 46.482 billion Chinese Yuan ( CNY ), which accounted for 0.22% of the Chinese gross domestic product ( GDP ) in 2006; the national cost–benefit ratio is 1:26. The regional cost–benefit ratios of the Chinese Public Weather Service exhibit a wide range from 1:2 to 1:81 over different provincial‐level regions. The cost–benefit ratios are much higher in economically developed areas (Central and East China) than in economically underdeveloped areas (Northwest China). The social development level, especially certain aspects of primary industry and transportation, is closely related to the cost–benefit ratio of the Chinese Public Weather Service. These findings can assist the China Meteorological Administration and its supervised meteorological bureaus in providing a weather service that meets the public needs effectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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