The Effects of Meditation and Visualization on the Direct Mental Influence of Random Event Generators
Bibliographic record
Abstract
Meditation and visualization exercises have been found to alter an individual’s mood and perception, and it is hypothesized that these techniques will enhance one’s ability to anomalously influence the function of a random event generator (REG) with the mind. This study is comprised of a control experiment and a second experiment with the administration of meditation and visualization exercises. There was no support for a significant deviation of the REG in the direction of the participants’ volition in Experiment 1, t(29) = -1.26, p = .22 (two-tailed), but results revealed a significant deviation in the intended direction in Experiment 2, t(29) = 2.66, p = .01 (two-tailed). Moreover, comparisons between cumulative deviations across both samples were found to be statistically significant, indicating that meditation and visualization exercises may promote significant deviations, t(58) = -2.69, p = .009 (two-tailed). These analyses suggest that the use of meditation and visualization techniques in experiments that study direct mental influence may be beneficial for finding anomalous effects. Keywords: meditation, visualization, random event generator, direct mental influence
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".