Cross-language transfer of word reading accuracy and word reading fluency in Spanish-English and Chinese-English bilinguals: Script-universal and script-specific processes.
Bibliographic record
Abstract
This study examined cross-language transfer of word reading accuracy and word reading fluency in Spanish–English and Chinese–English bilinguals. Participants included 51 Spanish–English and 64 Chinese–English bilinguals. Both groups of children completed parallel measures of phonological awareness, rapid automatized naming, word reading accuracy, and word reading fluency in their first language (L1) and in English, their second language (L2) in Grade 1. Word reading accuracy and word reading fluency were assessed in L1 and L2 again in Grade 2. Cross-language transfer of word reading accuracy was found only in the Spanish–English bilinguals. In contrast, cross-language transfer of word reading fluency was found in both the Spanish–English bilinguals and the Chinese–English bilinguals. Our results suggest transfer of word reading accuracy is based on the structural similarities between the L1 and L2 scripts. By contrast, word reading fluency operates largely as a script-universal process. Implications for reading theory and for assessment and instruction of bilingual children 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".