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Record W2884731980 · doi:10.5539/ijel.v8n6p61

The Elicitation of Verbal Humor in Total Women: Conversational Implicature and Relevance

2018· article· en· W2884731980 on OpenAlexvenueno aff
Rongbin Wang, Yaoqin Xue

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsnot available
FundersNational Office for Philosophy and Social Sciences
KeywordsRelevance (law)PresumptionImplicaturePsychologyNonverbal communicationRelevance theoryInterpretation (philosophy)InferenceConversationPragmaticsCognitive psychologyLinguisticsCommunicationComputer scienceCognitionArtificial intelligence

Abstract

fetched live from OpenAlex

This research examines how conversational implicature and relevance in communication contribute to the elicitation of verbal humor in Total Women, and it discusses whether the pragmatic theoretical analysis of verbal humor can eventually be induced to a hierarchical two-stage processing like Incongruity-resolution. It is shown that (1) The fun-making character Fannie’s statements which flouted different maxims of conversation all built up and led to the elicitation of verbal humor; (2) Relevance-eliciting verbal humor resembled to Incongruity-resolution with the oppositeness between the first interpretation and the retrieved one communicating the presumption of optimal relevance on the one hand and the humorous inference on the other hand.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.327
Teacher spread0.316 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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