Water reuse perceptions of students, faculty and staff at Western University, Canada
Bibliographic record
Abstract
Global fresh water resources are under increasing pressure from rapidly growing demands and changing climatic conditions. Wastewater reclamation is becoming an important alternative for sustainable water resources management and building climate change resiliency in many regions around the world. Public acceptance and trust of consumers in the quality of reclaimed water is considered by many to be the most important factor determining the outcomes of water reclamation projects. Knowledge of the urban water cycle and water reuse perceptions of student, faculty and staff at Western University were investigated. Results showed that members of the university community are more likely to accept reclaimed wastewater for applications that do not involve drinking or close personal contact. Knowledge of the urban water cycle and water resources in Canada is modest among the university community with a moderate (G = 0.303, p < 0.05) positive relationship between ‘water knowledge’ and ‘close contact acceptability’. The majority of the university community (75.8%) thinks that reclaiming water to provide an alternate source of water in southwestern Ontario is a good idea, but there are still concerns about the presence of chemicals such as pharmaceuticals from reclaimed water and the long-term effects on human health from exposure to these contaminants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".