What is the best way to characterise the contributions of oral language to reading comprehension: listening comprehension or individual oral language skills?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Educators and researchers agree that oral language is fundamental to students' reading acquisition. It is not clear how best to conceptualise oral language within models of reading – as one's overall understanding of spoken language, or as individual skills, each with unique contributions to children's reading comprehension. In our longitudinal study of children in Grades 2 and 3, we examined the unique contributions of three oral language skills – vocabulary, syntactic awareness, and morphological awareness – to gains in reading comprehension assessed later that academic year ( N = 116) and in the spring of the following academic year ( N = 87). In our most conservative analyses, we controlled for children's listening comprehension in addition to prior reading achievement. Each language skill predicted variance in later reading comprehension beyond that accounted for by initial word reading and reading comprehension. In analyses with listening comprehension also controlled, each of syntactic awareness and morphological awareness retained their predictive power. Morphological awareness emerged as the most robust predictor and was associated with greater increases in reading comprehension for students in third versus second grade. Results support theoretical models that identify and differentiate contributions from individual oral language skills to reading comprehension. Our findings suggest that increasing each of these oral language skills within the elementary classroom may lead to advances in children's reading comprehension.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it