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Record W2079563482 · doi:10.1075/gest.2.1.02bav

An experimental study of when and how speakers use gestures to communicate

2002· article· en· W2079563482 on OpenAlexaff
Janet Beavin Bavelas, Christine Kenwood, Trudy Johnson, Bruce Phillips

Bibliographic record

VenueGesture · 2002
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGestureVocabularyPsychologyRedundancy (engineering)CommunicationLinguisticsCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

This experiment expanded the visual availability paradigm by subsuming it under the broader principle of recipient design. We varied recipient design by asking speakers to describe a picture to someone who would see a videotape of their description or only hear an audiotape. Second, speakers described pictures that varied in verbal encodability. Finally, in addition to gestural rate, we analysed the redundancy of gestures with words. The results (N = 40) confirmed our predictions that speakers gesture at a higher rate and use a higher proportion of nonredundant gestures when their recipient would see their videotape; that they also use more nonredundant gestures when describing a picture for which they have a poor vocabulary; and that these two factors interact to produce the strongest effects when vocabulary is limited and the recipient would see the videotape. These effects support the hypothesis that speakers design their gestures to communicate to recipients.

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)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.102
GPT teacher head0.349
Teacher spread0.247 · 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 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

Citations77
Published2002
Admission routes1
Has abstractyes

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