How is Etuaptmumk/Two-Eyed Seeing characterized in Indigenous health research? A scoping review
Bibliographic record
Abstract
Our scoping review sought to consider how Etuaptmumk or Two-Eyed Seeing is described in Indigenous health research and to compare descriptions of Two-Eyed Seeing between original authors (Elders Albert and Murdena Marshall, and Dr. Cheryl Bartlett) and new authors. Using the JBI scoping review methodology and qualitative thematic coding, we identified seven categories describing the meaning of Two-Eyed Seeing from 80 articles: guide for life, responsibility for the greater good and future generations, co-learning journey, multiple or diverse perspectives, spirit, decolonization and self-determination, and humans being part of ecosystems. We discuss inconsistencies between the original and new authors, important observations across the thematic categories, and our reflections from the review process. We intend to contribute to a wider dialogue about how Two-Eyed Seeing is understood in Indigenous health research and to encourage thoughtful and rich descriptions of the guiding principle.
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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 | 0.087 | 0.230 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.019 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".