Phonological and lexical effects in verbal recall by children with specific language impairments
Bibliographic record
Abstract
BACKGROUND & AIMS: The present study examined how phonological and lexical knowledge influences memory in children with specific language impairments (SLI). Previous work showed recall advantages for typical adults and children due to word frequency and phonotactic pattern frequency and a recall disadvantage due to phonological similarity among words. While children with SLI have well-documented memory difficulties, it is not clear whether these language knowledge factors also influence recall in this population. METHODS & PROCEDURES: Sixteen children with SLI (mean age = 10;2) and chronological age-matched typically developing children (CAM) controls recalled lists of words differing in phonological similarity, word frequency and phonotactic pattern frequency. While previous studies used a small set of words appearing in multiple word lists, the current study used a larger set of words, without replacement, so that children could not gain practice with individual test items. OUTCOMES & RESULTS: All main effects were significant. Interactions revealed that children with SLI were affected by similarity, but less so than their peers, comparably affected by word frequency and unaffected by phonotactic pattern frequency. CONCLUSIONS & IMPLICATIONS: Results due to phonological similarity suggest that children with SLI use less efficient encoding, while results due to word frequency and phonotactic pattern frequency were mixed. Children with SLI used coarse-grained language knowledge (word frequency) comparably with peers, but were less able to use fine-grained knowledge (phonotactic pattern frequency). Paired with phonological similarity results, this suggests that children with SLI have difficulty establishing robust phonological knowledge for use in language tasks.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".