The consistency of the subjective concept of randomness
Bibliographic record
Abstract
A pervasive bias in the subjective concept of randomness is that people often expect random sequences to exhibit more alternations than produced by genuine random processes. What is less known is the stability of this bias. Here, we examine two important aspects of the over-alternation bias: first, whether this bias is present in stimuli that vary across feature dimensions, sensory modalities, presentation modes and probing methods, and, second, how consistent the bias is across these stimulus variations. In Experiment 1, participants adjusted sequences until they looked maximally random. The sequences were presented as temporal streams of colors, shapes, auditory tones or tiled as spatial matrices. In Experiment 2, participants produced random matrices by adjusting the color of each cell. We replicated the findings using a within-subjects design in Experiment 3. We found that participants judged and produced over-alternating stimuli as the most random. Importantly, this bias was consistent across presentation modes (temporal vs spatial), feature dimensions (color vs shape), sensory modalities (visual vs auditory), speed (fast vs slow), stimulus size (small vs large matrices) and probing methods (adjusting the generating process vs individual bits). Overall, the results suggest that the subjective concept of randomness is highly stable across stimulus variations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".