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Record W4311872927 · doi:10.1093/shm/hkac057

Tune in, Turn on: Religious Music and Spiritual Power in the History of Psychedelic Therapy

2022· article· en· W4311872927 on OpenAlexafffund
Stephen Lett, Erika Dyck

Bibliographic record

VenueSocial History of Medicine · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSet (abstract data type)Subject (documents)AestheticsPsychotherapistPower (physics)Session (web analytics)PsychologyTranceMusic therapySociologyArtComputer scienceBusinessAdvertising

Abstract

fetched live from OpenAlex

Psychedelic-assisted therapy has attracted considerable clinical attention in the past decade for its ability to bring therapeutic benefits to patients in treatment-resistant categories. In contradistinction from other psychopharmaco-therapies, contemporary psychedelic therapists, like their predecessors, paid close attention to the 'set and setting', and argued that the mind-set of the subject and the conditions or environment of the session was as influential as the pharmacological reaction itself. In this paper, we examine how religious sounds and music were both incorporated into and strategically avoided in the early psychedelic therapeutic sessions in an effort to achieve spiritual epiphanies at peak experiences. Prominent contemporary practices, we conclude, recapitulate many of the practices of the past, relying, we argue, on aesthetic premises that could hinder the therapy's broader applicability.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.024
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.074
GPT teacher head0.326
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2022
Admission routes2
Has abstractyes

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