Lexical Diversity Versus Lexical Error in the Language Transcripts of Children With Developmental Language Disorder: Different Conclusions About Lexical Ability
Bibliographic record
Abstract
Purpose The purpose of this study was to provide preliminary data on differences in lexical diversity and lexical-semantic errors in the language samples of children with developmental language disorder (DLD) and children with typical language development (TLD) of the same age. Method We analyzed word use in the narrative transcripts of children with DLD and TLD ( N = 14; M age = 6;8 [years;months]) using standard measures of lexical diversity (number of different words, moving-average type–token ratio) and additional counts of lexical-semantic errors. Results There were no significant differences between the groups in lexical diversity, and all children with DLD scored within the age-appropriate range on diversity relative to a normative sample. The children with DLD, however, produced significantly more lexical errors than their TLD peers. Conclusions The results suggest that caution is warranted when interpreting normal-range lexical diversity scores in children with DLD, as children with DLD may demonstrate functional difficulties with word use that are not captured by lexical diversity measures. A focus on lexical errors holds promise for characterizing lexical-semantic qualities of language transcripts that are not captured by standard measures of diversity. Development of a reliable clinical system for coding and characterizing lexical-semantic errors in language transcripts is warranted.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".