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Record W2049063548 · doi:10.3389/fpsyg.2014.01267

Speech in action: degree of hand preference for grasping predicts speech articulation competence in children

2014· article· en· W2049063548 on OpenAlexafffund
Claudia L. R. Gonzalez, Fangfang Li, Kelly J. Mills, Nicole Rosen, Robbin Gibb

Bibliographic record

VenueFrontiers in Psychology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Lethbridge
KeywordsGesturePsychologyLateralization of brain functionArticulation (sociology)Hand preferenceCognitive psychologyGRASPSpeech productionLanguage productionCompetence (human resources)LateralityPreferenceCommunicationCognitionDevelopmental psychologyLinguisticsSpeech recognitionComputer scienceSocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

HIGHLIGHTS: Degree of lateralization for grasping predicts the maturity of the language production system in young, typically-developing children. In this report we provide compelling evidence for the relationship between right hand grasp-to-mouth (i.e., feeding) movements and language development. Specifically, we show that children (4-5 years old) who are more right-hand lateralized in picking up small food items for consumption show enhanced differentiation of the "s" and "sh" sounds. This result suggests that left hemisphere control of hand-to-mouth gestures may have provided an evolutionary platform for the development of language. The current investigation presents the exciting possibility that early right hand-to-mouth training could accelerate the development of articulation skills.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.103
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.075
GPT teacher head0.325
Teacher spread0.250 · 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

Citations12
Published2014
Admission routes2
Has abstractyes

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