Study Protocol: The Effect of Bilingual Exposure on Linguistic and Cognitive Recovery Following Stroke
Bibliographic record
Abstract
This is the study protocol for the "The effect of bilingual exposure on language and cognitive recovery in children following stroke" project. Protocol Summary - Children with pediatric stroke face complex cognitive and linguistic challenges due to the sensitive timing of the stroke occurrence during the child’s development. Literature in typically developing bilinguals has shown that bilingual learning environments promote positive neural and cognitive development, affording certain linguistic and cognitive advantages. Whether this is the case and may affect enhanced recovery in children with atypical development is still unknown. The purpose of this study is to determine how bilingual exposure affects cognitive and linguistic recovery in children following pediatric stroke, by looking at differences in performance on outcome measures between the bilingual pediatric stroke group with respect to patient variables (sex, family history/education), stroke variables (age at stroke onset, location, laterality) and linguistic variables (language background). Medical charts will be reviewed to identify bilingual patients and compare their performance to monolingual patients based on their Pediatric Stroke Outcome Measure (PSOM) performance, sourced from the institutional stroke registry. Growth curve analyses on subscales of the PSOM, with respect to patient, stroke and linguistic variables (language background). Additionally, a case study will be conducted on a bilingual and monolingual patient, comparing their neuropsychological assessment scores.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.118 | 0.023 |
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".