Two-Eyed Seeing in Knowledge Synthesis: Weaving together Western scoping review methods with Indigenous storytelling to explore Indigenous approaches to harm reduction
Bibliographic record
Abstract
Using methodological approaches rooted in Indigenous ways of knowing and being can help to ensure that research findings are relevant and useful to Indigenous communities, while providing evidence for more responsive public health policy and practice. This article explores a practical application of a Two-Eyed Seeing approach in knowledge synthesis as part of Phase I of the First Nation Health Authority’s Indigenizing Harm Reduction Study. The Study aims to develop a First Nations harm reduction framework rooted in community knowledges in response to the disproportionate harms of the toxic drug emergency on First Nations people in British Columbia (BC). Our approach prioritized Indigenist research methods, centering relationality and storytelling in knowledge gathering, analyses, and validation activities, while weaving in a Western scoping review methodology. The literature review explored harm reduction among Indigenous communities globally. Conversational interviews and questionnaires gathered knowledge from individuals who identified as First Nations people who access harm reduction services or individuals who provide harm reduction services to First Nations people in BC. Weaving together these knowledge systems helped our team to develop a more wholistic understanding of existing harm reduction approaches and current needs of First Nations communities in BC, grounded in Indigenous values and lived experiences. This culturally relevant approach to knowledge synthesis contributes to the knowledge base on Indigenous research methodologies and presents a practical Two-Eyed Seeing framework for weaving together both academic and community-based evidence within healthcare contexts. We share this methodology as an offering for both Indigenous and settler scholars, care providers, and decision makers working in health to privilege Indigenous knowledges in developing evidence-informed policies and practices.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".