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Record W4384153518 · doi:10.3389/fpsyg.2023.1129428

Confronting the figure of the “mad scientist” in psychedelic history: LSD’s use as a correctional tool in the postwar period

2023· article· en· W4384153518 on OpenAlexaffabout
A. Jones

Bibliographic record

VenueFrontiers in Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnthusiasmContext (archaeology)PsychologyPeriod (music)PsilocybinStigma (botany)HallucinogenAestheticsSocial psychologyPsychiatryHistoryArt

Abstract

fetched live from OpenAlex

Since reports about CIA-funded LSD studies came out in the 1970s, psychedelic drugs have invoked images of unethical experimentation and “mad scientists” in the public imagination. Even now, as the stigma surrounding psychedelics diminishes in the 21st century, the figure of the “mad scientist” continues to occupy a space in what Ido Hartogsohn calls the “collective set and setting,” the larger framework of cultural understandings that shape how individuals experience psychedelic drugs. Scientists and humanities scholars who study these drugs have responded to this issue by drawing boundaries between those who used psychedelics carefully and those who used them ignorantly. Yet these boundaries were not always so clear in the past. Drawing on historical examples of LSD’s use as a correctional tool in Canada, I show how enthusiasm about the drug’s potential led several experienced and knowledgeable psychedelic therapists to use it on vulnerable populations in diverse institutional settings, such as correctional facilities. These examples reveal how the institutional context of modern industrial societies shaped the application of psychedelic therapy in the past and suggest that today’s therapists need to carefully consider how this broader context impacts their work.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.338
Teacher spread0.290 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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