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Record W2768779302 · doi:10.1002/dev.21583

ERPs reveal weaker effects of spelling on auditory rhyme decisions in children than in adults

2017· article· en· W2768779302 on OpenAlexafffund
Suzanne E. Welcome, Marc F. Joanisse

Bibliographic record

VenueDevelopmental Psychobiology · 2017
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsOntario Brain InstituteWestern University
FundersCanadian Institutes of Health ResearchOntario Innovation Trust
KeywordsRhymeOrthographyN400PsychologyPsycholinguisticsSpellingReading (process)AudiologyEvent-related potentialLinguisticsDevelopmental psychologyCognitive psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

A classic finding in psycholinguistics is that orthographic form influences the processing of auditory words. The aim of the present study was to examine how reading experience changes this effect. Specifically, we tested the prediction that top-down visual modulation of spoken word recognition is reduced in children compared to adults, owing to their reduced experience with print. Event-related potentials (ERPs) were measured as 8-10-year-old children and adults made rhyme decisions about spoken word pairs that were either orthographically similar or dissimilar. When orthography did not conflict (e.g., throat-boat), both age groups demonstrated a robust rhyme effect marked by greater N400 to no-rhyme versus rhyme trials. For rhyming trials that differed in orthography (e.g., vote-boat) and non-rhyming trials that shared orthography (e.g., warm-farm), adults showed more interference than children. Differences in orthographic interference suggest an extended developmental schedule for top-down mechanisms in speech recognition.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.304
Teacher spread0.291 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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