Infrastructure Alone is Not Enough: Identifying Gaps in the Literature Regarding First Nations Water Governance
Bibliographic record
Abstract
In 2015, the federal government committed to ending drinking water advisories in First Nations communities across Canada by 2021. Their approach involves an increase in monetary commitments to improving water quality infrastructure in priority First Nations communities. The perception surrounding water-based infrastructure investments in First Nations communities is that infrastructure grants will solve the issues related to boil water advisories and allow for all individuals in communities to access clean water. While the investments are overdue and necessary, infrastructure alone does not address the institutional issues related to governance of water for First Nations reserves. Furthermore, as Indigenous peoples have constitutionally protected Aboriginal and treaty rights, and international rights (e.g. UNDRIP) of which many are tied to safe water, Indigenous peoples are seeking to incorporate Indigenous laws into their local water governance systems. The goal of this research is to examine gaps in the literature related to First Nations water governance and policy and investigate alternative models of community level water governance. Focusing in Ontario, this research will investigate, the historical context which influences current water governance and created the framework for water management in First Nations communities. By identifying gaps in the planning and implementation projects, this research aims to add to the toolkit of potential solutions and improve the holistic approach to water management within First Nations communities across Ontario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".