The Timing Tells the Tale: Multiple Morphological Processes in Children’s and Adults’ Spelling
Bibliographic record
Abstract
Purpose Despite abundant evidence that morphemes are important in reading and spelling, little is known about the nature of processing in spelling. This study identifies multiple morphological processes over the time course of spelling, revealing that these processes are influenced by development.Method Twenty adults and 46 children (8;0–12;1 years) completed an auditory lexical decision task followed by a spelling task, to explore the effects of morphological structure and cross-modal morphological priming by analyzing handwriting latencies before and during spelling production.Results Adults and children both demonstrated morphological processing during lexical access – they were faster to begin to write morphologically complex words (e.g., artist) compared to matched monomorphemic controls (e.g., article). Adults (but not children) also demonstrated cross-modal morphological priming. Further, adults (but not children) demonstrated the effects of morphological processing during spelling production. Inter-letter latencies were shorter between the last two letters of a root morpheme than the same letters in monomorphemic control words (e.g., ar[]tist compared to ar[]ticle).Conclusion Together, these findings reflect multiple facilitative effects of morphological processing during spelling production – during lexical access and spelling production. This highlights the need for greater integration of morphological processes into theories of skilled spelling and spelling development.
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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 | 0.005 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".