Co-development of a risk assessment tool for use in First Nations water supply systems: A key step to water safety plan implementation
Bibliographic record
Abstract
Despite several years of targeted interventions, First Nations drinking water systems in Canada remain under-resourced and require substantial improvements in both infrastructure and management to provide communities with safe drinking water. The purpose of this study was to co-develop a risk assessment process integral to the water safety planning methodology to determine if proactive risk assessment provides a beneficial management tool for First Nations water systems. We co-developed a risk assessment web-application with First Nations stakeholders to identify hazards and assess risk in six Atlantic region First Nations communities. Using this application, we were able to successfully identify high-risk hazards in each community, both risks specific to individual systems, and risks common at a regional level. Through semi-structured interviews we identified the following benefits of a risk assessment web application: increased communication, data ownership and centralized data management. However, challenges remain, including current fragmented governance realities, and liability concerns associated with adopting a new risk management strategy. Successful adoption of proactive risk management strategies in First Nations communities will depend on strong co-development of risk assessment tools, transparent communication between stakeholders and clearly defined data ownership and management practices.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".