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Record W2164444422 · doi:10.1044/lle22.2.42

Gestures Occur With Spatial and Motoric Knowledge: It's More Than Just Coincidence

2015· article· en· W2164444422 on OpenAlexaff
Autumn B. Hostetter, Elina Mainela‐Arnold

Bibliographic record

VenuePerspectives on Language Learning and Education · 2015
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGesturePsychologyFacilitationCognitive psychologyCognitionFocus (optics)Nonverbal communicationSpeech productionMotion (physics)CommunicationComputer scienceSpeech recognitionArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Representational gestures are hand and arm movements that are related to the semantic content of co-occurring speech. In this review, we present evidence that such movements not only provide insight into the knowledge possessed by a speaker, but also provide insight into how that knowledge is represented. Specifically, gestures often occur with the communication of information that is understood spatially or motorically but that has not yet been verbally or linguistically encoded. Using gesture to convey such information can have a number of benefits for speakers, including facilitation of speech production processes and reduction of cognitive load. We focus our review on evidence from individual differences in gesture production among both typical and clinical populations, and conclude with a few recommendations for language therapists who are interested in using gesture as a tool in their practice.

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)0.001
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.006
Scholarly communication0.0040.008
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.379
Teacher spread0.351 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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