Environmental Multifunctionality of Paddy Fields in Taiwan- A Conjunction Evaluation Method of Contingent Valuation Method and Analytic Network Procedures
Bibliographic record
Abstract
This study uses the benefit and value assessment method, in conjunction with a Contingent Valuation Method (CVM) and Analytic Network Procedures (ANP), through the use of questionnaires, to assess the preference structure and relative weight scales that are assigned to the multifunctionality function and production output benefits that are derived from paddy fields. The monetary benefits associated with the multifunctionality of paddy fields are as below:1) Benefits from production are NT$20.97 (NT$1 about US$0.03385) (US$0.71), from 1kg of rice, 2) Benefits to food safety and reliance are NT$36.38 (US$1.23), from 1kg of rice, 3) Benefits to cultural heritage and community development are NT$13.51 (US$0.46), from 1kg of rice, 4) Benefits to recreation and landscape are NT$12.34(US$0.42), from 1kg of rice, and 5) Benefits to environmental conservation are NT$25.4(US$0.86), from 1kg of rice. The ratio of nonmarket/rice production is 4.18. The monetary benefits constitute the gross domestic product (GDP), for rice production. These benefits from all five categories constitute the green gross domestic product (Green GDP), for rice production. This study calculated the Green GDP, for rice production, which included the market price of rice production and the non-market value of the multifunctionality of paddy fields, which generated NT$158 billion (US$5.3483 billion), in 2008. The ratio of rice production output to real production output, as defined by this study, obtained a result close to 1(0.97), showing that the benefit assessment for market goods and non-market goods, in conjunction with ANP and CVM, is a reliable assessment method, which should be promoted in the future.
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How this classification was reachedexpand
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 | 0.008 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".