Describing the Unspeakable: Psychedelic Communication Technologies and the Development of a Posthuman Language
Bibliographic record
Abstract
ABSTRACT Over the last three decades, the renaissance of interdisciplinary research into psychedelic drugs has challenged the Cartesian notions of subjectivity and identity that have endured throughout modernity. But as work in this field reaches new degrees of complexity, the limitations of verbal and textual language are presenting barriers to conventional forms of scholarship. Across the disciplines, qualitative researchers mapping the subjective dimensions of the psychedelic experience, both in themselves and in others, must grapple with the ineffable nature of these transpersonal states of consciousness. To address these roadblocks, this paper introduces a new way of thinking about the neurological and phenomenological effects of the classic psychedelics DMT, LSD, and psilocybin. By interpreting neuroscientific research on these compounds using ideas from Gilles Deleuze and Felix Guattari’s Capitalism and Schizophrenia series, I argue that they can be understood not only as spiritual sacraments, psychoactive molecules, and healing medicines, but also as communication technologies that prime the human brain for higher-dimensional forms of language production. I begin by describing the effects that psychedelics have on normal human brain functioning, with an overview of contemporary neuroscientific research. Next, I introduce Deleuze and Guattari’s concepts of deterritorialization and stratification, which I argue can bring the subjective and empirical dimensions of the psychedelic experience together in a single descriptive framework. After a brief overview of contemporary psychedelic philosophy, I conclude by exploring how these molecules are playing a role in the development of multisensory (and posthuman) forms of language.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.030 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".