A scoping review of strengths-based drinking water policies in Indigenous communities in Canada, the United States, New Zealand, and Australia
Bibliographic record
Abstract
The Indigenous Peoples of Australia, Canada, New Zealand, and the United States have faced a shared history of disenfranchisement under settler-colonial paradigms. One consequence of this marginalization has been the widespread deprivation of secure access to safe drinking water in Indigenous communities. To date, much of the literature on Indigenous drinking water access has taken a deficit-based approach, focusing on the factors that are “lacking” from Indigenous communities. Deficit-based approaches have been criticized for perpetuating cycles of negative experiences, fostering dependency within the target community, and leading to interventions that are unsustainable and limited in scope. In contrast, this scoping review comprised a strengths-based investigation of successful Indigenous drinking water policy in Australia, Canada, New Zealand, and the United States. Through this review of the gray literature published from 2000 to 2024, we identified methods for measuring the success of Indigenous drinking water policies; common features of Indigenous drinking water policies said to be successful; and external factors which have been found to contribute to the success of Indigenous drinking water policies. The subsequent thematic analysis revealed a need to leverage the assets within Indigenous communities, drawing upon the strengths inherent to traditional knowledge systems and cultural practices, by involving Indigenous Peoples as key stakeholders in the development of drinking water policy. There is an opportunity for policymakers to engage in an iterative process that considers the larger problems we have identified in this review, as well as the community-specific concerns of the Indigenous groups being served.
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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 | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.036 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 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".