The psychedelic renaissance and the limitations of a White-dominant medical framework: A call for indigenous and ethnic minority inclusion
Bibliographic record
Abstract
In recent years, the study of psychedelic science has resurfaced as scientists and therapists are again exploring its potential to treat an array of psychiatric conditions, such as depression, post-traumatic stress disorder, and addiction. The scientific progress and clinical promise of this movement owes much of its success to the history of indigenous healing practices; yet the work of indigenous people, ethnic and racial minorities, women, and other disenfranchised groups is often not supported or highlighted in the mainstream narrative of psychedelic medicine. This review addresses this issue directly: first, by highlighting the traditional role of psychedelic plants and briefly summarizing the history of psychedelic medicine; second, through exploring the historical and sociocultural factors that have contributed to unequal research participation and treatment, thereby limiting the opportunities for minorities who ought to be acknowledged for their contributions. Finally, this review provides recommendations for broadening the Western medical framework of healing to include a cultural focus and additional considerations for an inclusive approach to treatment development and dissemination for future studies.
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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 | 0.036 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.034 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".