A Critical Review of Water Reuse in North America: The Historical Shift from Technological Priorities to Public Perception Studies
Bibliographic record
Abstract
Water reuse is an increasingly popular consideration for municipalities, developers, and businesses. Currently, the majority of water reuse applications originate from Australia, Southeast Asian nations, and the Middle East. Stresses posed by population growth and/or water scarcity seem to be the primary drivers for the prevalence of reuse applications in these regions. However, an increasing number of regions in North America are in the process of implementing or have already implemented some form of water reuse. As a result, this paper aims to present an overview of the history and current state of reuse in North America, with the objective of defining past and current challenges, gaps in current research, and necessary steps for more robust reuse applications. Ultimately, the paper critically assesses the trajectory of reuse projects in North America from the 1970s onwards; highlighting the gradual shift in focus from technological feasibility to public perception studies associated with water reuse.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| 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".