Challenges to Environmental Valuation of Water in Light of Global Change
Bibliographic record
Abstract
Abstract A number of challenges are faced by practitioners seeking to elicit values associated with water in a world of global change. These values are needed to assist in decision-making around the use of water as a country’s key asset. Five different pathways show the complexity of the relationship between global change and environmental valuation of water: a climate change pathway, ecosystem infrastructure pathway, population/demographics pathway, income pathway, and technological change/innovation pathway. The challenges are most acute for water when it is related to ecosystem services since values need to be elicited through the use of non-market survey-based valuation techniques. In addition, environmental valuation will be important to inform the determination of water quality standards associated with different uses of water (drinking, recreation, etc.) and the allocation of resources to provide these different services. Several case studies illustrate issues and solutions. The article concludes with an appreciation of future challenges and opportunities.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".