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Record W4395664330 · doi:10.1111/mbe.12411

Neural Activation during Phonological Processing in <scp>Primary‐School</scp> Children with Limited Reading Experience: Insights from Rural Côte d'Ivoire

2024· article· en· W4395664330 on OpenAlexaff
Kaja Kinga Jasińska, Shakhlo Nematova, Henry Brice, Xinyi Yang

Bibliographic record

VenueMind Brain and Education · 2024
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Toronto
FundersJacobs Foundation
KeywordsPsychologyReading (process)NeuroimagingDevelopmental psychologyLiteracyPhonologyReciprocalPhonological awarenessDyslexiaCognitive psychologyNeuroscienceLinguistics

Abstract

fetched live from OpenAlex

Abstract Phonological awareness (PA) is an important predictor and outcome of reading. Yet, little is known about the reciprocal relation between PA and reading across development without consistent reading experience (e.g., as a result of limited access to quality education and late enrolment in school). We tested the hypothesis that variable reading experience in childhood influences neural activation in regions involved in language and reading processing—left frontal and temporoparietal cortex. Sixty‐nine primary‐school children ( M age = 10.4) from rural low‐literacy communities in Côte d'Ivoire completed a PA task while undergoing functional near‐infrared spectroscopy neuroimaging (fNIRS) neuroimaging and a reading battery. We observed differences in left inferior frontal and bilateral temporoparietal activation for younger versus older children with similar reading skills, suggesting neural activations for phonological processing depends on the age when children have reading experience. Without consistent access to quality education, children may miss out on reciprocal interactions between phonological processing and reading shaping language processing in the brain.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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 teacher head, 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

Citations4
Published2024
Admission routes1
Has abstractyes

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