The colors of the alphabet: Naturally-biased associations between shape and color.
Bibliographic record
Abstract
Many letters of the alphabet are consistently mapped to specific colors in English-speaking adults, both in the general population and in individuals with grapheme-color synaesthesia who perceive letters in color. Here, across six experiments, we tested the ubiquity of the color/letter associations with typically developing toddlers, literate children, and adults. We found that pre-literate children associate O with white and X with black and discovered that they also associate I and ameboid nonsense shapes with white; Z and jagged nonsense shapes with black; and C with yellow; but do not make a number of other associations (B blue; Y yellow; A red; G green) seen in literate children and adults. The toddlers' mappings were based on the shape and not the sound of the letter. The results suggest that sensory cortical organization initially binds specific colors to some specific shapes and that learning to read can induce additional associations, likely through the influence of higher order networks as letters take on meaning.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".