Knowledge influences perception: Evidence from the Ebbinghaus illusion
Bibliographic record
Abstract
A fundamental question in cognitive science is the relation between knowledge and perception: does our knowledge of the world influence the way we see it? To help answer this question, we used the Ebbinghaus illusion, in which a circle looks larger when surrounded by smaller circles than when surrounded by larger ones. Unlike circles, coins - such as quarters or dimes - have a fixed size, and we predicted that such knowledge of object constancy would weaken the perceptual illusion. A hundred observers reported the apparent size of a quarter when surrounded by dimes, and when surrounded by one-dollar coins. The apparent size of the quarter was compared to the apparent size of a circle when surrounded by small circles, and when surrounded by big circles. Consistent with our hypothesis, the illusion was weakened for coins. We interpret this result to suggest that visual perception is influenced by semantic knowledge, such as the knowledge of coins as objects of invariant size.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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; both teacher heads agree on what is shown here.
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".