Operator‐informed risk assessment tool: Opportunities and barriers to support risk management practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Successfully implementing water safety plans (WSPs) in small, municipal drinking water systems is understudied in affluent jurisdictions where WSPs are not required by regulations. We piloted a computer‐based risk assessment survey in eight municipal water systems in Nova Scotia, Canada to evaluate the benefits and challenges of implementing risk assessment strategies in non‐WSP jurisdictions. Semi‐structured interviews were conducted with water operators and managers to gather feedback on the risk assessment survey and process. Results indicated difficulties quantifying risk despite streamlining the risk identification process, resulting in key informants viewing the risk assessment as strictly diagnostic and unlikely to be integrated into operational practice if not required. We identified a need to shift water system culture from a regulatory‐based to a knowledge‐based mindset for successful risk assessment implementation. Clear lines of communication, increased understanding of risk, and commitment to improvement are critical to shifting water system culture toward a risk‐based water quality management approach.
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.
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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it