Western Households’ Water Knowledge, Preferences, and Willingness to Pay
Bibliographic record
Abstract
Water conflicts are intensifying as the population grows in the American West. Stakeholders seek a better understanding of households’ water knowledge, preferences, and willingness to pay (WTP) as they contemplate various water allocation initiatives. An Internet survey provides insight into western households’ perceptions and preferences regarding water use and management, their familiarity with water terminology, and their WTP a fee in support of eight potential water initiatives regarding water acquisition, conservation, and reallocation. Further analysis identifies factors that influence the decision. Just over half of all respondents express a WTP the fee, with an estimated median WTP among survey respondents of $15.65 per summer month. Respondents with higher self‐reported water knowledge are more likely to support the fee. The probability of supporting the fee is also influenced by respondents’ demographic characteristics and attitudes toward water scarcity and management. Les conflits liés à l’eau s’intensifient à mesure que la population s’accroît dans l’Ouest américain. Les parties prenantes cherchent à découvrir les connaissances sur l’eau, les préférences et le consentement à payer des ménages étant donné qu’elles envisagent divers schémas d’allocation de l’eau. Un sondage en ligne a donné un aperçu des perceptions et des préférences des ménages de l’Ouest américain concernant l’utilisation et la gestion de l’eau, de leur degré de connaissance de la terminologie de l’eau et de leur consentement à payer une taxe pour appuyer huit projets éventuels d’acquisition, de conservation et de réallocation de l’eau. Une analyse plus détaillée a déterminé les facteurs qui influençaient les décisions. Un peu plus de la moitié des répondants ont indiquéêtre prêts à payer une taxe. Chez les répondants, le consentement à payer médian s’élevait à 15,65 $ par mois durant la saison estivale. Les répondants qui ont indiqué avoir de bonnes connaissances sur l’eau sont plus susceptibles d’appuyer l’imposition d’une taxe. Les caractéristiques démographiques et les attitudes des répondants envers la rareté et la gestion de l’eau influencent la probabilité d’appuyer l’imposition d’une taxe.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".