Two-eyed seeing as a philosophy to facilitate communication between indigenous counselors and psychiatry about mind and mental health
Bibliographic record
Abstract
Introduction The term “two-eyed seeing” is spreading across North America as a concept for explanatory pluralism. The concept was brought into academic science by Albert Marshall, a M’iqmaq from Nova, Scotia, Canada. It speaks to the idea that indigenous knowledge is an equally valid way of conceptualizing a phenomenon as is contemporary science. Marshall’s famous example compares a traditional M’iqmaq story about the origins of the large tides in the Bay of Fundy with contemporary oceanographic geology findings and simulations. Objectives We wanted to explore how this two-eyed seeing model could be applied to mental health to facilitate a dialogue between psychiatry and traditional cultural healers. Methods We reviewed the existing literature on two-eyed seeing within mental health care using PubMed, IndexMedicus, OneSearch, and Google Scholar. We presented a course on two-eyed seeing for indigenous mental health services and two-eyed seeing for addressing trauma in indigenous communities and surveyed the participants about the two-eyed seeing concept. We offered this course primarily to providers within indigenous communities and also for other interested counsellors. Results Participants in our trainings were enthusiastic about the role of two-eyed seeing for improving communication among indigenous providers and patients and non-indigenous providers. Most indigenous counselors had not heard of two-eyed seeing and were quite enthusiastic about its affirming nature and how it gave them a basis for dialogue with non-indigenous practitioners. Conclusions Two-eyed seeing allows a rich dialogue between European-derived practitioners and indigenous people that enabls each to appreciate the other’s perspectives, leading to greater cooperation and collaborative treatment. Disclosure No significant relationships.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".