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Record W2504773786 · doi:10.1080/02791072.2016.1202459

A Public-Health-Based Vision for the Management and Regulation of Psychedelics

2016· article· en· W2504773786 on OpenAlexaff
Mark Haden, Brian Emerson, Kenneth W. Tupper

Bibliographic record

VenueJournal of Psychoactive Drugs · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsMinistry of HealthUniversity of British Columbia
Fundersnot available
KeywordsCorporate governanceHarmPublic healthWork (physics)Set (abstract data type)Key (lock)Public administrationHarm reductionBusinessPublic relationsPolitical scienceEnvironmental healthCriminologyPsychologyComputer securityMedicineLawComputer scienceEngineeringNursingFinance

Abstract

fetched live from OpenAlex

The Health Officers Council of British Columbia has proposed post-prohibition regulatory models for currently illegal drugs based on public health principles, and this article continues this work by proposing a model for the regulation and management of psychedelics. This article outlines recent research on psychedelic substances and the key determinants of benefit and harm from their use. It then describes a public-health-based model for the regulation of psychedelics, which includes governance, supervision, set and setting controls, youth access, supply control, demand limitation, and evaluation.

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)0.037
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.100
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0070.062
Scholarly communication0.0170.008
Open science0.0040.008
Research integrity0.0170.025
Insufficient payload (model declined to judge)0.0040.001

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 head0.076
GPT teacher head0.383
Teacher spread0.307 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations31
Published2016
Admission routes1
Has abstractyes

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