Source Water Protection in Rural Newfoundland and Labrador: Limitations and Promising Actions
Bibliographic record
Abstract
The purpose of this paper is to exemplify through recent research in Newfoundland and Labrador (NL) the extent of the current limitations for source water protection and potential opportunities for improvement in the province, particularly for rural communities. The findings of this paper draw from the results of four related studies led by the co-authors. These four studies took place in NL between 2012 and 2016, and derived data through a mixed-method approach using literature reviews, key informant interviews, surveys, and consultations. The article provides an overview of the state of source water protection in NL and the challenges faced, with case examples to illustrate key points. Findings indicate there is currently a source water protection gap in NL limiting local governments in implementing their source water protection obligations under provincial policy and regulations. This implementation gap has been attributed to a lack of capacity for watershed monitoring, a lack of awareness of the need for source water protection and of municipal responsibilities, conflicts over multi-use watersheds and a lack of watershed planning and management. Greater education and collaboration in source water protection efforts amongst all watershed users, watershed groups, local governments and the provincial government could offer promise to fill this gap.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".