Looking Upstream: Findings from Focus Groups on Public Perceptions of Source Water Quality in British Columbia, Canada
Bibliographic record
Abstract
In association with the development of new microbial tests for source water quality (SWQ), focus groups with members of the public were conducted to gain insight into their perceptions of SWQ, behaviours and contaminants they think pose the greatest threat to its quality, and what/how they want to know about SWQ. Discussions revealed a low concern about SWQ in general, and in particular about microbial contamination. Participants identified behaviours that threaten SWQ, barriers to changing behaviour and suggestions for inducing change. A strong desire was expressed for water quality information to be interpreted and communicated in terms of how SWQ may impact human health and how their actions should be altered in response to test results. The information can be used to inform communication strategies and possibly impact policies associated with water quality testing and implementation of new tests. More broadly, awareness of the public's understanding and beliefs about source water can be used in working with the public to adopt water-friendly behaviours, influence the content and methods of communicating with the public about water issues and water quality, and could contribute to the direction of future research and investment into water technologies to align with the public's priorities.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".