Sipping the virtual elixir: An autoethnographic close reading of Ayahuasca Kosmik Journey, a self-transcendent virtual experience
Bibliographic record
Abstract
Self-transcendent experiences are often an integral component of ancient cultural practices that use psychedelic substances during spiritual ceremonies, such as ayahuasca ceremonies. Yet, ayahuasca contains dimethyltryptamine (DMT), which is illegal in many countries. Due to its illegality, ayahuasca experiences are scarce despite potential benefits of increased quality of life and reduced psychopathology. Virtual reality (VR) can provide a safe and legal glimpse of psychedelic experiences, such as an ayahuasca ceremony. These experiences may in turn evoke self-transcendent emotions without hallucinogenic substances, extending the power of art and technology to stimulate self-transcendence. To explore the potential, limits and experiential qualities that immersive experience design can afford for cyberdelic experiences, we conducted an autoethnographic close reading analysis of Atlas V’s Ayahuasca Kosmik Journey. Autoethnography allowed us to study complex and personal experiences while close reading connected those experiences to the design of the artefact. This allowed us to gain insights into the connections between design and experience and critically analyse the experience. The resulting reflection unveiled prominent psychological lenses in our subjective experience, including agency, embodiment, discomfort and self-transcendent emotions. Our analysis explicates the paramount role of spatiality, the sensorium and theme with embodied interaction for the self-transcendent effects of vastness, the role of contrast in narrative transitions and how meaning is rooted in previous experiences. Our analysis unveils the potential and the limitations of immersive technology to emulate self-transcendent experiences through extending our senses and transcending the self.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".