Examining policy implementation gaps in source water protection in Newfoundland and Labrador
Bibliographic record
Abstract
Source water protection (SWP) has gained importance in the literature related to water resources, with the general knowledge that drinking water sources can be more easily, economically and safely guarded from pollution through SWP than by remedying water sources after they have been contaminated. In addition to the actions of citizens, SWP requires policy commitments from government including regulatory activity. However, results of prior studies have suggested that gaps exist between policy and regulations and the reality of practices in communities of rural Newfoundland and Labrador (NL). Previous studies suggest that these gaps are due to the limitations in various kinds capacity at both local and provincial levels but suggest that further research is needed to better understand these limitations within the NL context. This research sought to identify the key factors in the context of NL that deter implementation of SWP measures and to explore options for addressing these factors. In particular barriers to implementation were examined using a four part capacity framework, including: institutional, technical/human, financial and social capacities. Data collection methods included document review, reanalysis of survey data and telephone interviews across six case study communities with varied levels of compliance to SWP policies and regulations. Data analysis was done through categorization and coding using Nvivo software followed by pattern analysis. As suggested in past research, areas of concern identified in this study include monitoring activities within protected water supply areas, uncertified drinking water operators, and limited watershed planning, because of limitations in local government’s ability to implement their SWP responsibilities under provincial regulations and policy. The study found deficiencies in all four capacity categories and contributes to enhancing the understanding of these challenges within SWP policy implementation and drinking water management in rural NL. Finally, the study’s recommendation for addressing implementation gaps in SWP policy and regulations in NL include: adequate financial support for SWP; expanded communication, education and awareness initiatives; increased community involvement and participation and collaboration among the various actors involved, and strengthening monitoring and enforcement efforts.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".