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Record W4389614071 · doi:10.3138/jmvfh-2023-0010

A history and future of psychedelics: The case of the Canadian military

2023· article· en· W4389614071 on OpenAlexaffvenueabout
Erika Dyck, Gregory P. Marchildon

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of TorontoUniversity of Saskatchewan
Fundersnot available
KeywordsPsilocybinLysergic acid diethylamidePsychologyPsychiatryMilitary personnelMAGIC (telescope)HallucinogenMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

LAY SUMMARY The historical relationship between psychedelic drugs and the military has often been characterized in terms of drug misuse or the connection between drugs like d-lysergic acid diethylamide (LSD) or psilocybin (magic mushrooms) contributing to anti-war sentiments. Recent clinical evidence, however, suggests these cultural associations may be overshadowing the potential for psychedelic drug treatments for particular disorders prevalent across military personnel, including posttraumatic stress disorder. This article offers a historical overview of psychedelics and their association with anti-war activism alongside the clinical recognition of mental disorders within the military that led to the need to reimagine the relationship between psychedelics and mental illnesses within the military.

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)0.001
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 score0.686
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.055
GPT teacher head0.333
Teacher spread0.278 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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