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Record W4386737170 · doi:10.35502/jcswb.339

Psychonautical engineering: Synergizing the magic of mindfulness, mushrooms, and mindsets for police officer well-being

2023· article· en· W4386737170 on OpenAlexfundvenueaboutno aff
Renae M. Stevenson

Bibliographic record

VenueJournal of Community Safety and Well-Being · 2023
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsnot available
FundersVancouver Island University
KeywordsMindfulnessMental healthPsychologyContemplationBattlePsychotherapistPolitical sciencePublic relationsHistory

Abstract

fetched live from OpenAlex

The setting of policing exposes its officers to a host of negative health outcomes physiologically, psychologically, and spiritually. Policing mindsets around accessing mental health are far from fixing the epidemic of its mental health crisis or being able to sustain a healthy workforce. Policing is losing the battle with a misguided and a scientifically misinformed war on drugs. Canadian legislators are shifting mindsets from decriminalizing substance use towards applying a public health lens to the mycelium underlying its root causes. So too should its peace officers—not just to restore peace in society—but also in their own minds and in their dysregulated nervous systems by synergizing psilocybin’s neural benefits with mindfulness-based psychotherapy. Western science’s exploration into the healing magic of mushrooms and mindfulness is in its infancy compared with the centuries of wisdom from both Indigenous science and eastern contemplative traditions. Not only does their fusion amplify hope for those suffering but perhaps it offers a scientific key to the neurogenesis of resilience. This is a pracademic trip driven by a retired and now reformed agent from Canada’s War on Drugs.

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 score0.599
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.018
GPT teacher head0.306
Teacher spread0.289 · 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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