Insights from the remote co‐creation of an Indigenous knowledge questionnaire about aquatic ecosystems in Kinngait, Nunavut
Bibliographic record
Abstract
Abstract There is growing interest in co‐developing research projects that more fully address the priorities of Indigenous communities throughout the Canadian Arctic and beyond. However, details regarding collaborative methods are often not adequately described in the literature. Here, we describe a process to remotely co‐create a questionnaire compiling Indigenous knowledge about local aquatic species and their habitats with the community of Kinngait, Nunavut. This project was undertaken in response to interest expressed by the Aiviq Hunters and Trappers Association in understanding and assessing the impacts of climate change on coastal ecosystems. Researchers from Fisheries and Oceans Canada and academic partners drafted an initial questionnaire that was revised through a series of collaborative sessions with community‐based technicians. We detail the stages of this process and discuss elements that enabled co‐creation including: adaptable and frequent communication, community technician roles, and a pre‐existing partnership. This paper emphasizes that project co‐development and the co‐creation of research tools can be a mutually beneficial process that can broaden our collective understanding of the impacts of climate change on Arctic aquatic ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 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".