Use of narratives to assess language disorders in an inpatient pediatric psychiatric population
Bibliographic record
Abstract
A large proportion of child psychiatry patients have undiagnosed language disorders. Adequately developed language is critical for psychotherapy and cognitive-behavioral therapies. This study investigated (1) whether assessment of oral narratives would identify language impairments in this population undetected by assessment of only core language abilities, and (2) the extent to which measures of cognition, working memory, emotional distress, and social function differentially predict core language and narrative development. Results showed that (1) more than twice as many children were identified with language impairment when both narrative and core language assessment were used, and (2) core language comprehension and complex verbal working memory were the strongest predictors of narrative production, while core language comprehension, a less complex working-memory task, and social skills best predicted narrative comprehension. Emotional distress did not predict either. The results emphasize the importance of evaluating child psychiatry patients' language, using both core language and narrative measures.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".