Discourse Macrolevel Processing After Severe Pediatric Traumatic Brain Injury
Bibliographic record
Abstract
The purpose of this study was to determine if discourse macrolevel processing abilities differed between children with severe traumatic brain injury (TBI) at least 2 years postinjury and typically developing children. Twenty-three children had sustained a severe TBI either before the age of 8 (n = 10) or after the age of 8 (n = 13). The remaining 32 children composed a control group of typically developing peers. The groups' summaries and interpretive lesson statements were analyzed according to reduction and transformation of narrative text information. Compared to the control group, the TBI group condensed the original text information to a similar extent. However, the TBI group produced significantly less transformed information during their summaries, especially those children who sustained early injuries. The TBI and control groups did not significantly differ in their production of interpretive lesson statements. In terms of related skills, discourse macrolevel summarization ability was significantly related to problem solving but not to lexical or sentence level language skills or memory. Children who sustain a severe TBI early in childhood are at an increased risk for persisting deficits in higher level discourse abilities, results that have implications for academic success and therapeutic practices.
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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 | 0.000 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".