The Effect of Bilingual Exposure on Language and Cognitive Development in Children Following Ischemic Stroke
Bibliographic record
Abstract
Abstract AIM While many children who experience ischemic stroke come from bilingual backgrounds, it is unclear whether bilingual exposure affects post-stroke development. Our research evaluates the effects of bilingual vs. monolingual exposure on linguistic/cognitive development post-stroke. METHOD An institutional stroke registry and medical charts were used to gather data on 237 children across 3 stroke-onset groups: neonatal - <28 days, first-year - 28 days to 12 months and childhood - 13 months to 18 years. The Pediatric Stroke Outcome Measure (PSOM) was administered at several times post-stroke, to evaluate cognition and linguistic development. RESULTS Bilingual children had better post-stroke performance on the language subscales, compared to monolinguals. An interaction with stroke-onset group was also observed, with monolinguals in the first-year group having worse outcomes. INTERPRETATION Overall, no detrimental effects of bilingualism were found on children’s post-stroke cognition and linguistic development. Our study suggests that a bilingual environment may facilitate language development in children post-stroke.
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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 | 0.004 |
| 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 | 0.000 |
| 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".