Psychedelics beyond medicine: Treatment, enhancement, hype, consent, and the limits of medicalization
Bibliographic record
Abstract
The current revival of interest in classic psychedelics and other psychoactives such as ketamine and MDMA, coupled with changes to their regulatory status in many jurisdictions, necessitates rigorous ethical guidelines both within and beyond clinical and scientific contexts. This paper examines crucial ethical, philosophical, and policy considerations needed to ensure psychedelic use across various settings remains equitable, beneficial, consensual, and safe, with appropriate accountability mechanisms for addressing potential harms. We seek to broaden the lens beyond the medical model of psychedelics to include potentially valuable non-medical applications that could benefit individuals, communities, and society. With popular interest in psychedelics growing outside of therapeutic and research settings, there is a need to determine which aspects of any proffered guidelines, or underlying principles, should be applied similarly across contexts and in what ways there should be flexibility and/or context-sensitivity in their interpretation or application. In developing such guidelines, we suggest the “treatment versus enhancement” distinction – and associated debates familiar from bioethics and philosophy of medicine – requires renewed attention. We argue that neglecting non-medical and broad scientific use cases for psychedelics may have important implications for a range of ethical issues surrounding psychedelic use and research, including concerns about psychedelic hype and exceptionalism (both positive and negative), therapeutic touch, informed consent, data-gathering, and balancing access and safety. We conclude with suggestions for future directions in research and policy in the burgeoning area of psychedelic bioethics, stressing the importance of incorporating the perspectives of a diversity of stakeholders and fostering cross-sector collaboration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".