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Record W4306983412 · doi:10.1017/s0305000922000423

Touching while listening: Does infants’ haptic word processing speed predict vocabulary development?

2022· article· en· W4306983412 on OpenAlexafffund
Kayla Beaudin, Diane Poulin‐Dubois, Pascal Zesiger

Bibliographic record

VenueJournal of Child Language · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsConcordia University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsVocabularyHaptic technologyTask (project management)Vocabulary developmentComprehensionActive listeningPsychologyStroop effectWord processingControl (management)Word (group theory)Speech recognitionComputer scienceCognitive psychologyArtificial intelligenceCommunicationLinguisticsCognition

Abstract

fetched live from OpenAlex

The present study examined the links between haptic word processing speed, vocabulary, and inhibitory control among bilingual children. Three main hypotheses were tested: faster haptic processing speed, measured by the Computerized Comprehension Task at age 1;11, would be associated with larger concurrent vocabulary and greater longitudinal vocabulary growth. Second, early vocabulary size would be associated with greater vocabulary growth at 3;0 and 5;0. Finally, faster haptic processing speed would be associated with greater concurrent inhibitory control, as measured by the Shape Stroop Task. The results revealed that haptic processing speed was associated with concurrent vocabulary, but not predictive of later language skills. Also, early decontextualized vocabulary was predictive of vocabulary at 3;0. Finally, haptic processing speed measured in the non-dominant language was associated with inhibitory control. These results provide insight on the mechanisms of lexical retrieval in young bilinguals and expand previous research on haptic word processing and vocabulary development.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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 designBench or experimental
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

Citations1
Published2022
Admission routes2
Has abstractyes

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