The influence of grapheme-color synaesthesia on eye movements
Bibliographic record
Abstract
Grapheme-color synaesthesia is a condition in which ordinary black text is perceived in vivid colors. Some grapheme-color synaesthetes report that they dislike looking at a grapheme that is presented in the “wrong” color (i.e. a color that is incongruent with their synaesthetic experiences for the grapheme). We investigated the ramifications of grapheme color congruency by monitoring eye movements. In Experiment 1, D.E., a grapheme-color synaesthete, searched displays of colored graphemes for a specific target letter. Each display contained equal numbers of congruently and incongruently colored graphemes. The target grapheme was present on half of the trials and absent on the other half of the trials. On target present trials, D.E. was more likely to miss and re-fixate incongruently colored targets than congruently colored targets. On target absent trials, there was a trend for D.E.'s overall fixation times to be greater on congruent items than on incongruent items. In Experiment 2, D.E. was asked to freely view displays of colored graphemes for as long as he wished. Again, congruent items received more fixation time than did incongruent items. These findings indicate that not only does D.E. dislike looking at “wrongly” colored graphemes, but he also tends to ignore information that is inconsistent with his synaesthetic experiences.
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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 | 0.008 |
| 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 | 0.000 |
| 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".