Mitigating Public Concerns About Recycled Drinking Water: Leveraging the Power of Voting and Communication
Bibliographic record
Abstract
Abstract This research studies the perceptions of individuals concerning reused drinking water. Individuals' visceral responses may stigmatize reused water as the water's immediate origin is too clear. In this context, we show how individuals grow more accepting of reused water when their decisions consider others, as opposed to just themselves. First, differences between private and public decision making are quantified using willingness to accept (WTA) data collected in economic experiments. Adult participants first made decisions in a second‐price auction (private rounds) followed by majority‐rule voting (public rounds) on the median price collected in the private rounds. Our results show that participants in the public rounds significantly reduce their WTA. Moreover, a communication treatment using chat boxes further reduced participants' WTA. The recorded chat indicated that particularly messages related to humor and persuasion were powerful influences on participants' voting decisions. The results have applications for sustainable, cost‐effective recycled water projects.
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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 | 0.003 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".