Role of Phonology in Reading: A Stroop Effect Case Report With Japanese Scripts
Bibliographic record
Abstract
An experiment investigated the role of phonological activation in Japanese adults’ reading of ideograms (Kanji) and syllabic characters (Kana), using the Stroop effect. A group of 21 native speakers of Japanese completed color-naming (Stroop) and word-naming (reverse-Stroop) tasks with Kanji and Kana characters. A series of analyses contrasted the reaction time required for different script types; including Kanji color words, Kanji homophones, and Kana. On the hypothesis that a word’s pronunciation plays an important role in its semantic activation process, it was predicted that color-naming/word-reading interference and facilitation would be demonstrated for both the Kanji color words and Kanji homophones, with Kanji homophones showing somewhat reduced effects. The results showed robust color-naming (Stroop) patterns for the Kanji color words, significant effects for Kana, and no significant Stroop effects for the Kanji homophones. A word-reading (reverse-Stroop) task revealed uniform effects of interference with incongruent stimuli across the three script types. Taken together, the data suggest different processing routes may be accessed in color-naming and word-reading tasks.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".