Cree-driven community-partnered research on coastal ecosystem change in subarctic Canada: a multiple knowledge approach
Bibliographic record
Abstract
Indigenous-driven and community-partnered research projects seeking to develop salient, legitimate, and credible knowledge bases for environmental decision-making require a multiple knowledge systems approach. When involving partners in addition to communities, diverging perspectives and priorities may arise, making the pathways to engaging in principled research while generating actionable knowledge unclear to disciplinarily-trained natural science researchers. Here, we share insights from the Eeyou Coastal Habitat Comprehensive Research Project (CHCRP), an interdisciplinary, Cree-driven community-academic partnership. This project brought together Cree community members, regional organizations, industry (Hydro-Québec), and academics from seven universities across Canada to address the unprecedented loss of seagrass Zostera marina (eelgrass), the concurrent decline in migratory Canada geese and its impact on fall goose harvest activities in Eeyou Istchee. After describing the history and context of the project, we discuss the challenges, complexities, and benefits of the collaborative approach balancing saliency, legitimacy, and credibility of the knowledge produced. We suggest the paper may be of use to researchers and partners seeking to engage in principled and actionable research related to environmental change including impacts of past development.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.008 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".