Children reading spoken words: interactions between vocabulary and orthographic expectancy
Bibliographic record
Abstract
There is an established association between children's oral vocabulary and their word reading but its basis is not well understood. Here, we present evidence from eye movements for a novel mechanism underlying this association. Two groups of 18 Grade 4 children received oral vocabulary training on one set of 16 novel words (e.g., 'nesh', 'coib'), but no training on another set. The words were assigned spellings that were either predictable from phonology (e.g., nesh) or unpredictable (e.g., koyb). These were subsequently shown in print, embedded in sentences. Reading times were shorter for orally familiar than unfamiliar items, and for words with predictable than unpredictable spellings but, importantly, there was an interaction between the two: children demonstrated a larger benefit of oral familiarity for predictable than for unpredictable items. These findings indicate that children form initial orthographic expectations about spoken words before first seeing them in print. A video abstract of this article can be viewed at: https://youtu.be/jvpJwpKMM3E.
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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 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".