Ask the pendulum: personality predictors of ideomotor performance
Bibliographic record
Abstract
For centuries, people have asked questions to hand-held pendulums and interpreted their movements as responses from the divine. These movements occur due to the ideomotor effect, wherein priming or thinking of a motion causes muscle movements that end up swinging the pendulum. By associating particular swinging movements with “yes” and “no” responses, we investigated whether pendulums can aid decision-making and which personality traits correlate with this performance. Participants (N=80) completed a visual detection task in which they searched for a target letter among rapidly presented characters. In the verbal condition, participants stated whether they saw the target in each trial. In the pendulum condition, participants instead mentally “asked” a hand-held pendulum whether the target was present; particular motions signified “yes” and “no”. We measured the accuracy of their responses as well as their sensitivity and bias using signal detection theory. We also assessed four personality measures: locus of control (feelings of control over one’s life), transliminality (sensitivity to subtle stimuli), need for cognition (preference for analytical thinking), and faith in intuition (preference for intuitive thinking). Overall, locus of control predicted verbal performance and transliminality predicted pendulum performance. Accuracy was low in both conditions (verbal: 57%, pendulum: 53%), but bias was higher in the verbal condition (d=1.10). We confirmed this bias difference in a second study (d=0.47, N=40). Our results suggest that people have different decision strategies when using a pendulum compared to conscious guessing. These findings may help explain why some people can answer questions more accurately with pendulums and Ouija boards. More broadly, identifying the differences between ideomotor and verbal responses could lead to practical ways to improve decision-making.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".