“Spirit, Safety, and a Stand-off ”: The Research-Creation Process and Its Roles in Relationality and Reconciliation among Researcher and Indigenous Co-Learners in Saskatchewan, Canada
Bibliographic record
Abstract
Provision of safe water on reserves is an ongoing problem in Canada that can be addressed by mobilizing water knowledge across diverse platforms to a variety of audiences. A participatory artistic animation video on the lived experiences of Elderswith water in Yellow Quill First Nation, Treaty Four territory, was created to mobilize knowledge beyond conventional peer-review channels. Research findings from interviews with 22 Elders were translated through a collaborative process into a video with a storytelling format that harmonized narratives, visual arts, music, and meaningful symbols. Three themes emerged which centered on the spirituality of water, the survival need for water, and standoffs in water management. The translation process, engagement and video output were evaluated using an autoethnographic approach with two members of the research team. We demonstrate how the collaborative research process and co-created video enhance community-based participatory knowledge translation and sharing. We also express how the video augments First Nations community ownership, control, access and possession (OCAP) of research information that aligns with their storytelling traditions and does so in a youth-friendly, e-compatible form. Through the evaluative process we share lessons learned about the value and effectiveness of the video as a tool for fostering partnerships, and reconciliation. The benefits and positive impacts of the video for the Yellow Quill community and for community members are discussed.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".