Transferrable Principles to Revolutionize Drinking Water Governance in First Nation Communities in Canada
Bibliographic record
Abstract
There are analogous challenges when it comes to the management and provision of health services and drinking water in First Nations reserves in Canada; both represent human rights and both involve complex and multijurisdictional management. The purpose of this study is to translate the tenets of Jordan’s Principle, a child-first principle regarding health service provision, within the broader context of First Nation drinking water governance in order to identify avenues for positive change. This project involved secondary analysis of data from 53 semi-structured, key informant (KI) interviews across eight First Nation communities in western Canada. Data were coded according to the three principles of: provision of culturally inclusive management, safeguarding health, and substantive equity. Failure to incorporate Traditional Knowledge, water worldviews, and holistic health as well as challenges to technical management were identified as areas currently restricting successful drinking water management. Recommendations include improved infrastructure, increased resources (both financial and non-financial), in-community capacity building, and relationship building. To redress the inequities currently experienced by First Nations when it comes to management of and access to safe drinking water, equitable governance structures developed from the ground up and embedded in genuine relationships between First Nations and Canadian federal government agencies are required.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".