Water security risks in small, remote, indigenous communities in Canada: A critical review on challenges and opportunities
Bibliographic record
Abstract
Abstract Indigenous communities in Canada are disproportionately affected by issues related to water security, especially access to clean water to meet human needs. The issues these communities face are diverse and widespread across Canada, with many causes and consequences. This review summarizes the types and magnitudes of risks associated with the water security of these communities, the consequences considering health and social perspectives, and the means of responding to these issues. Risks are broadly divided into quantitative risks (e.g., water quality and availability) and qualitative risks (e.g., lack of funding and jurisdictional conflicts). These risks lead to unique consequences, resulting in challenges in developing generalized risk response frameworks. Management of these risks includes a mix of techniques relying on legislative and technical approaches. Nevertheless, the affected communities should be included in the decision-making process that should be holistic, incorporating indigenous knowledge. Good governance, cooperation between communities, policy improvement and the development of an institutional mechanism for clean water supply will provide a pathway and guidelines to address the water security challenges among indigenous communities.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".