The capacity gap: Understanding impediments to sustainable drinking water systems in rural Newfoundland and Labrador
Bibliographic record
Abstract
This article outlines the results of a two-year research project that examined drinking water challenges in rural and small-town Newfoundland and Labrador. A mixed-methods approach was used, including literature review, media scans, a driver-pressure-state-impact-response analysis, policy workshops, community surveys and consultations, case studies and key informant interviews. This interdisciplinary study examined four interrelated components of drinking water systems: source water quality and quantity; water infrastructure and operations; public perception, awareness and demand; and policy and governance. Issues identified include: aging, degrading and inappropriate infrastructure; high disinfectant by-products; use and misuse of chlorine; long-term boil water advisories; use of untreated water sources; and minimal source water protection. As other studies have found elsewhere in Canada, local actors in Newfoundland and Labrador communities of 1000 or fewer often exhibit inadequate technical/human, social, institutional and financial capacity to address their drinking water challenges. New water policies and governance arrangements are needed that emphasize strategic and efficient investments, including the utilization of regional approaches, long-term planning and asset management activities. Furthermore, greater focus is needed on capacity development and the engagement and education of decision makers, staff, the public, and other groups that can help local governments address their drinking water challenges.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".