Processing Speed Measures as Clinical Markers for Children With Language Impairment
Bibliographic record
Abstract
PURPOSE: This study investigated the relative utility of linguistic and nonlinguistic processing speed tasks as predictors of language impairment (LI) in children across 2 time points. METHOD: Linguistic and nonlinguistic reaction time data, obtained from 131 children (89 children with typical development [TD] and 42 children with LI; 74 boys and 57 girls) were analyzed in the 3rd and 8th grades. Receiver operating characteristic curve analyses and likelihood ratios were used to compare the diagnostic usefulness of each task. A binary logistic regression was used to test whether combined measures enhanced diagnostic accuracy. RESULTS: In 3rd grade, a linguistic task, grammaticality judgment, provided the best discrimination between LI and TD groups. In 8th grade, a combination of linguistic and nonlinguistic tasks, rhyme judgment and simple response time, provided the best discrimination between groups. CONCLUSIONS: Processing speed tasks were moderately predictive of LI status at both time points. Better LR+ than LR- values suggested that slow processing speed was more predictive of the presence than the absence of LI. A nonlinguistic processing measure contributed to the prediction of LI only at 8th grade, consistent with the view that nonlinguistic and linguistic processing speeds follow different developmental trajectories.
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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 | 0.006 | 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 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".