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Record W4412063825 · doi:10.1016/j.bandl.2025.105612

Effects of object familiarity on children’s silent gestures

2025· article· en· W4412063825 on OpenAlexafffund
Elena Nicoladis, Josiah Goetze

Bibliographic record

VenueBrain and Language · 2025
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of AlbertaUniversity of British Columbia Hospital
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsPsychologyObject (grammar)GestureDevelopmental psychologyCognitive psychologyNeurotypicalContrast (vision)Argument (complex analysis)CommunicationLinguisticsAutism

Abstract

fetched live from OpenAlex

When gesturing (with or without speech) actions done with objects, young children and adults with apraxia often produce a body-part-as-object (BPO), like an extended finger for a toothbrush. In contrast, older children and neurotypical adults often produce an imagined object (IO), like pretending to hold a toothbrush. The purpose of this study was to test whether IOs are produced when children have a rich conceptual understanding of the functions of an object. If so, children should produce more IOs (relative to BPOs) with familiar than with unfamiliar objects. Children between three and five years old were asked to demonstrate what to do with either familiar or unfamiliar objects. As predicted, the children produced more IOs with familiar than unfamiliar objects. These results are consistent with the argument that children's handshape when gesturing reflects the richness of their understanding. Developmental change likely occurs as children develop a rich understanding of many objects.

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)0.002
metaresearch head score (Gemma)0.018
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.301
Teacher spread0.296 · 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
Published2025
Admission routes2
Has abstractyes

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