Water Insecurity in Ontario First Nations: An Exploratory Study on Past Interventions and the Need for Indigenous Water Governance
Bibliographic record
Abstract
In 2018, I began an exploratory study involving fourteen Ontario First Nation participants that examined some First Nation water security challenges and opportunities. In acknowledgment that many of the government assessments, reports, and investments to date have failed, this study aims to determine the causes of the water crisis as well as potential solutions by sharing Indigenous perspectives and recommendations on water governance and security. During the study, Indigenous participants were asked interview questions regarding their water and wastewater systems, their historical and current water security conditions, and if they had recommendations for achieving water security in First Nations. The analysis from these interviews demonstrated that there were ten different themes for water security and insecurity in First Nation communities as well as a set of four recommendations shared by the fourteen participants. The participant recommendations are: (1) that Traditional Knowledge (TK) and Indigenous laws be included in water security initiatives and water governance; (2) that provincial and federal governments work with Indigenous communities on their water security challenges and opportunities; (3) that First Nation leadership develops and implements community water protection plans; (4) that Indigenous communities establish an oversight committee or body for monitoring tourist ventures and extractive development projects such as mining on their territories. This paper will also discuss how an Indigenous research paradigm can be applied during the research process to ensure that the information is captured from the Indigenous perspectives of the participants.
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 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 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".