Keeping the promise: a critique of the current state of microdosing research
Bibliographic record
Abstract
Introduction: The practice of taking small, sub-hallucinogenic doses of psychedelics, known as microdosing, has exploded in popularity over the last decade. Users claim benefits ranging from improved mood and enhanced creativity to an increased sense of meaning and connectedness in life. While research on microdosing is still lagging behind the shift in public opinion, several papers have been published in the last five years which attempted to assess the effects of microdosing. Methods: This review paper aimed to critically analyze the research practices used in the recent wave of microdosing research: We reviewed 15 papers published before the closing date of this review in March 2022. Results: Our review concludes that it is premature to draw any conclusions about the efficacy or safety of microdosing since the research quality cannot be considered confirmatory. Discussion: We propose some potential causes for the current state of the literature and some suggestions for how these causes may be ameliorated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.142 | 0.219 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.002 | 0.024 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".