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Record W2580808226 · doi:10.3968/9033

Mitigating Mechanism of Discourse Markers

2016· article· en· W2580808226 on OpenAlexvenueno aff
Qianbo Li

Bibliographic record

VenueCanadian social science · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitenessContradictionEmotivePoliteness theoryInterpersonal communicationMechanism (biology)Face (sociological concept)Discourse markerSocial psychologyRelation (database)LinguisticsPsychologySociologyEpistemologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Of all the discourse markers functioning in discourse, mitigators are pointed out as one of the significant pragmatic categories among all the discourse markers. Fraser (1980) initiates the topic of mitigation and reveals its intimacy with politeness. Caffi (1999) further points out that mitigation is functional to smooth the speech acts that may impose face threat to the interlocutors, for instance, risks of self-contradiction, refusal, losing face, conflict and so forth. Under these circumstances, DMs with mitigating force serve as good candidates for monitoring interpersonal relation, emotive distance between interlocutors.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.281
Teacher spread0.251 · 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 designTheoretical or conceptual
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

Citations4
Published2016
Admission routes1
Has abstractyes

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