Cross-script transfer of word reading fluency in a mixed writing system: Evidence from a longitudinal study in Japanese
Bibliographic record
Abstract
ABSTRACT We examined the cross-lagged relations between word reading fluency in the two orthographic systems of Japanese: phonetic (syllabic) Hiragana and morphographic Kanji. One hundred forty-two Japanese-speaking children were assessed on word reading fluency twice in Grade 1 (Times 1 and 2) and twice in Grade 2 (Times 3 and 4). Nonverbal IQ, vocabulary, phonological awareness, morphological awareness, and rapid automatized naming were also assessed in Time 1. Results of path analysis revealed that Time 1 Hiragana fluency predicted Time 2 Kanji fluency after controlling for the cognitive skills. Time 2 Hiragana fluency did not predict Time 3 Kanji fluency or vice versa after the autoregressor was controlled, but Hiragana and Kanji fluency were reciprocally related between Times 3 and 4. These findings provide evidence for a cross-script transfer of word reading fluency across the two contrastive orthographic systems, and the first evidence of fluency in a morphographic script predicting fluency development in a phonetic script within the same language.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".