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Pragmatic Constraints on Gesture Use: The Effect of Downward and Non Entailing Contexts on Gesture Processing

2011· book-chapter· en· W59536351 on OpenAlexaff
Gianluca Giorgolo, Stephanie Needham

Bibliographic record

VenueLecture notes in computer science · 2011
Typebook-chapter
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsCarleton University
Fundersnot available
KeywordsGestureComputer scienceMaximInterpretation (philosophy)Extension (predicate logic)Gesture recognitionNatural language processingHuman–computer interactionCognitive scienceLinguisticsArtificial intelligenceEpistemologyProgramming languagePsychologyPhilosophy

Abstract

fetched live from OpenAlex

We report on ongoing research on the semantic and pragmatic factors that influence the interpretation of co-speech spontaneous gestures. We extend the semantic theory introduced by Giorgolo in [1] by proposing a pragmatic principle that controls the felicitousness of spontaneous gestures in different linguistic contexts. The principle is based on the idea of rationality in communication and will result in an extension of the gricean Maxim of Quantity [2]. We also present an experiment that we designed to test the predictions of the combined semantico-pragmatic principles.

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)0.022
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 score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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
Published2011
Admission routes1
Has abstractyes

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