Are morphological awareness and literacy skills reciprocally related? Evidence from a cross-linguistic study.
Bibliographic record
Abstract
We examined the direction of the relation between morphological awareness and reading/spelling skills in 2 languages varying in orthographic consistency (English and Greek) and whether word reading fluency and vocabulary mediate the relation between morphological awareness and reading comprehension. One-hundred and 59 English-speaking Canadian and 224 Greek children were assessed 4 times between Grades 1 and 3 on measures of morphological awareness, phonological awareness, word reading fluency, and spelling to dictation. Vocabulary was assessed at the end of Grade 2 and reading comprehension at the end of Grade 2 and at the beginning of Grade 3. Cross-lagged analyses showed that earlier morphological awareness predicted later reading comprehension and spelling in both languages and reading fluency in English. The effect of morphological awareness on reading comprehension was not mediated by word reading fluency in either language, but an indirect effect through vocabulary emerged in English. Earlier reading fluency and spelling predicted later morphological awareness before Grade 3 only in English, but morphological awareness began to predict spelling as early as Grade 1 in Greek. Multigroup analyses further showed that the effects of morphological awareness on reading fluency and the effects of spelling on morphological awareness were stronger in English than in Greek. Theoretical implications of these findings are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".