Attitudes toward water resilience and potential for improvement
Bibliographic record
Abstract
Abstract Non-technical summary There is a global water crisis, brought on by human actions. The ways we make decisions about water must transform to solve it. We focused on the attitudes that people in society hold toward water to understand how close or far away we are from a broadly accepted worldview that supports this transformation (what we call ‘water resilience’). We found that, across six countries in the Global South and North, attitudes showed moderate support for water resilience. Many people also showed potential to increase their support. Technical summary Water in the Anthropocene is threatened. Water governance aligned with the complex, dynamic, and uncertain nature of social–ecological systems (a ‘water resilience’ paradigm) is needed, and requires transformative change. We queried the potential for transformative change from the perspective that societal worldviews/paradigms offer an important leverage point for system change. Our study aimed to identify attitudes about water resilience and the extent to which there was potential for greater endorsement of water resilience. We surveyed individuals in six countries using vignettes to determine their level of water resilience endorsement (n = 2649). Overall water resilience endorsement was moderate (M = 2.86 out of 4). In some countries, a vignette related to a personally relevant water issue resulted in higher water resilience endorsement. More than half of the respondents held the potential for greater water resilience endorsement. Those with the greatest potential were younger, had children, considered religion more important, were more likely to live in urban areas, and lived in the same area for 10+ years. These findings provide guidance how to engage with the public (e.g. age-specific or parent-focused framing) to potentially increase societal water resilience endorsement. Social media summary General public in six countries moderately supports water resilience to address the water crisis, with room to improve.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".