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Record W2008801360 · doi:10.1075/gest.13.1.03bav

Reconciling the effects of mutual visibility on gesturing

2013· article· en· W2008801360 on OpenAlexafffund
Janet Beavin Bavelas, Sara Healing

Bibliographic record

VenueGesture · 2013
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGestureVisibilitySignificant differenceAffect (linguistics)PsychologyControl (management)Cognitive psychologyLinguisticsSocial psychologyCommunicationComputer scienceArtificial intelligenceMathematicsPhilosophyStatisticsGeography

Abstract

fetched live from OpenAlex

Fourteen visibility experiments, which compared the overall rate of gesturing when participants could or could not see each other, have produced perfectly contradictory results: Seven found a significantly higher overall gesture rate in the visible condition, and seven found no significant difference. Experiments that used quasi-dialogues in which the addressees’ responses were experimentally constrained (e.g., using a confederate) found a significant difference; the experiments that used free dialogues did not. This review examined three possible explanations and found that (1) the use of quasi-dialogues did not ensure better experimental control, (2) the constrained addressees may have introduced a confound that could account for the significant difference, and (3) although mutual visibility did not affect the overall gesture rate in free dialogues, it significantly increased more specific features of gestures that are useful to addressees. These findings raise several issues about the utility of conventional visibility designs for understanding conversational gestures.

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)0.024
metaresearch head score (Gemma)0.054
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: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.004
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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

Citations34
Published2013
Admission routes2
Has abstractyes

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