Indigenous Voices in Psychedelic Therapy: Experiential Learnings from a Community-Based Group Psychedelic Therapy Program
Bibliographic record
Abstract
Novel and traditional psychedelic medicines are attracting interest as potential treatments of mental illness. Before psychedelic therapies can be made available in culturally safe and effective ways to diverse peoples, the field must grapple with the complex legacies of colonialism and ongoing clashes between biomedical and Indigenous Ways of Knowing. This article presents results of a pilot program offering group-based therapy augmented by three sessions of ketamine at a psychedelic dose, for a group of Indigenous participants. This unique project was undertaken in partnership between Roots to Thrive and the Snuneymuxw First Nation to assess this approach's effectiveness and safety for Indigenous peoples. Thematic analysis of qualitative interviews and anonymous feedback received throughout the program from eight participants and two Elders provided rich information on participant motivations, perceived barriers, appreciated and beneficial aspects of the program, and the psychedelic experiences, as well as important directions for further improvement. In addition to challenges, participants attributed significant benefits to the program while highlighting the importance of the involvement of Indigenous team members, the incorporation of traditional approaches to healing, and the cultivation of open and authentic relationships between group participants and facilitators. We discuss important lessons learned and the essential work of reconciliation in, and beyond, psychedelic therapies.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".