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Record W7065515700

The Effect of Bilingual Exposure on Language and Cognitive Recovery in Children following Stroke

2021· dissertation· W7065515700 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsStroke (engine)CognitionNeuroscience of multilingualismExpressive languageStroke recoveryAphasiaOutcome (game theory)
DOInot available

Abstract

fetched live from OpenAlex

Pediatric stroke often affects higher-level cognition and linguistic processes. Certain linguistic and cognitive advantages have been confirmed in behavioural studies of typically developing bilingual children. This research evaluates the effects of bilingual exposure on linguistic/cognitive recovery in children post-stroke. In Study 1, an interaction effect between language group and stroke-onset group revealed that bilinguals 1-12 months at stroke onset had better expressive language compared to monolinguals, based on the Pediatric Stroke Outcome Measure administered at several points post-stroke. In Study 2, a monolingual-bilingual pair of children aged 78 at stroke onset were compared using language/cognitive assessments in a case study. Results taking relative change over time in account showed similarities to Study 1, with the bilingual case having a more consistent recovery of expressive language. Overall, no negative effect of bilingualism on development after stroke was found; rather there may be an expressive linguistic advantage post-stroke outcome for bilingual patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.283
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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