Seeking Substantiality: Evaluation of Public Attitudes toward Resilient Wastewater Reuse Management
Bibliographic record
Abstract
Because of Iran's limited water resources, maximum usage of available water resources is a high priority. In this case study of Tehran, Iran, academic and industrial applications of the strengths, weaknesses, opportunities and threats (SWOT) approach provide an analysis of the main challenges of wastewater reuse. One possible solution for dealing with water crises is to reuse water in different consumption areas. An important step in this regard is to evaluate the public attitude toward different usages of recycled water, and to increase public participation in this process. In addition, questionnaires offer quantitative analysis of people's preferences with respect to wastewater reuse. The results suggest that the Tehran water department should consider defensive approaches to developing public participation in wastewater reuse. The main underlying reasons people are in favour of wastewater reuse are the provision of environmental protection from contamination caused by wastewater and irrigating farmlands of non-food products.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".