“I Can Read These Colors.” Orthographic Manipulations and the Development of the Color-Word Stroop
Bibliographic record
Abstract
The color-word Stroop is a popular measure in psychological assessments. Evidence suggests that Stroop performance relies heavily on reading, an ability that improves over childhood. One way to influence reading proficiency is by orthographic manipulations. To determine the degree of interference posed by orthographic manipulations with development, in addition to standard color-Words (purple) we manipulated letter-positions: First/last letter in correct place (prulpe) and Scrambled (ulrpep). We tested children 7-16 years (n = 128) and adults (n = 23). Analyses showed that Word- and First/last-incongruent were qualitatively similar, whereas Word-congruent was different than other conditions. Results suggest that for children and adults, performance was hindered the most for incongruent and incorrectly spelled words and was most facilitated when words were congruent with the ink color and correctly spelled. Implications on visual word recognition and reading are discussed.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".