The Colour of Os: Naturally Biased Associations between Shape and Colour
Bibliographic record
Abstract
Many letters of the alphabet are consistently mapped to specific colours by English-speaking adults, both in the general population and in individuals with grapheme-colour synaesthesia who perceive letters in colour. Such associations may be naturally biased by intrinsic sensory cortical organisation, or may be based in literacy (eg 'A' is for 'apple', apples are red; therefore A is red). To distinguish these two hypotheses, we tested pre-literate children in three experiments and compared their results to those of literate children (aged 7-9 years) and adults. The results indicate that some colour letter mappings (O white, X black) are naturally biased by the shape of the letter, whereas others (A red, G green) may be based in literacy. They suggest that sensory cortical organisation initially binds colour to some 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 | 0.000 | 0.003 |
| 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 | 0.000 |
| 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".