Relationships Among Rapid Digit Naming, Phonological Processing, Motor Automaticity, and Speech Perception in Poor, Average, and Good Readers and Spellers
Why this work is in the frame
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Bibliographic record
Abstract
In this article, we explore the relationship between rapid automatized naming (RAN) and other cognitive processes among below-average, average, and above-average readers and spellers. Nonsense word reading, phonological awareness, RAN, automaticity of balance, speech perception, and verbal short-term and working memory were measured. Factor analysis revealed a 3-component structure. The first component included phonological processing tasks, RAN, and motor balance. The second component included verbal short-term and working memory tasks. Speech perception loaded strongly as a third component, associated negatively with RAN. The phonological processing tests correlated most strongly with reading ability and uniquely discriminated average from below- and above-average readers in terms of word reading, reading comprehension, and spelling. On word reading, comprehension, and spelling, RAN discriminated only the below-average group from the average performers. Verbal memory, as assessed by word list recall, additionally discriminated the below-average group from the average group on spelling performance. Motor balance and speech perception did not discriminate average from above- or below-average performers. In regression analyses, phonological processing measures predicted word reading and comprehension, and both phonological processing and RAN predicted spelling.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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