Reconciling How We Live With Water: The Development and Use of a Collaborative Podcasting Methodology to Explore and Share Diverse First Nations, Inuit, and Métis Perspectives
Bibliographic record
Abstract
Conventional approaches to water research and governance often fail to meaningfully engage and mobilize Indigenous peoples’ perspectives, values, and knowledge in addressing water-related concerns. This research introduces the use of collaborative podcasting as a methodological approach, applied in the context of this work to explore First Nations, Inuit, and Métis perspectives around how we live with, and relate to, water in Canada; and what the inclusion of these perspectives mean for water policy and research. Data were collected during a National Water Gathering event through sharing circle dialogue and participant interviews (n=18), and contributed to the creation of an audio-documentary podcast. Thematic analysis revealed key themes relating to: responsibilities to water; confronting colonialism; and pathways to mobilizing diverse knowledge systems. Findings from this work illustrate how relationships with, and responsibilities to, water are being sustained, reclaimed, and renewed by Indigenous people, and the value and power inherent in such actions.
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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 | 0.034 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".