MétaCan
Menu
Back to cohort
Record W2755594403 · doi:10.5430/elr.v6n3p27

Conversational Storytelling in Chinese Speech Acts

2017· article· en· W2755594403 on OpenAlexvenueno aff

Bibliographic record

VenueEnglish Linguistics Research · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsStorytellingNarrativeExpression (computer science)Point (geometry)Face (sociological concept)LinguisticsSpeech actPsychologyCommunicationObject (grammar)SociologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Conversational narrative or storytelling is a prevalent activity in everyday talk. This paper, drawing on the speech act theory and conversational analysis methodology, examines the conversational storytelling in performing a few types of illocutionary acts like assert, warn, object, advise in Chinese everyday talk. It is found that storytelling plays several significant roles in performing some types of illocutionary acts, i.e. to make a point, to build rapport among friends and even to reduce the face threat. Conversational storytelling may occur immediately after the expression of an illocutionary act, and sometimes before it to indicate certain illocutionary force.

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)0.002
metaresearch head score (Gemma)0.038
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.149
GPT teacher head0.414
Teacher spread0.265 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Linguistics ResearchSame topicLanguage, Discourse, Communication StrategiesFrench-language works237,207