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Record W3081352606 · doi:10.1086/707512

Reframing Bummer Trips: Scientific and Cultural Explanations to Adverse Reactions to Psychedelic Drug Use

2020· article· en· W3081352606 on OpenAlexaff
Erika Dyck, Chris Elcock

Bibliographic record

VenueThe Social History of Alcohol and Drugs · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTRIPS architectureHarmAnxietyPsychologyCriminologyCognitive reframingPublic healthPsychotherapistPsychiatrySocial psychologyMedicine

Abstract

fetched live from OpenAlex

The concept of a bad or bummer trip has been used to capture the imagination of public health advisors and drug regulators, especially for producing warnings against taking drugs that cause physical and psychological harm. Psychedelics emerged in the 1960s public health literature as frequently causing bad trips, with violent and fearful outbursts from users causing harm to themselves and others. The fear and anxiety allegedly generated by a chemical reaction in the body, however, was understood differently by contemporary psychedelic scientists in the 1950s and 1960s. Confronting fear or facing trauma played an important role in psychotherapy, and psychedelic therapists offered an alternative interpretation on the bad trip that imbued it with healthful benefits. This article considers the historical tension surrounding the competing interpretations of bummer trips, probing more deeply into the implications of avoiding fear, trauma, or anxiety in the psychotherapeutic encounter. Ultimately, by considering cases presented at different psychedelic clinics in North America and comparing those with news, personal testimonies, and regulatory outcomes in the United States, we argue that the specter of the bad trip was used strategically to galvanize public support for a prohibition on psychedelics. Moreover, by removing psychedelics from active research, the field of psychotherapy in some jurisdictions moved away from addressing core ideas about fear and trauma through confrontation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.355
Teacher spread0.251 · 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 teacher head, 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

Citations28
Published2020
Admission routes1
Has abstractyes

Explore more

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