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Record W4225401165 · doi:10.17507/tpls.1205.05

A Cross-Cultural Study of Modality in the Speech Act of Asking for Permission

2022· article· en· W4225401165 on OpenAlexaboutno aff
Tien B. Tran

Bibliographic record

VenueTheory and Practice in Language Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsVietnamesePolitenessLinguisticsVariation (astronomy)PsychologyModality (human–computer interaction)Speech actStyle (visual arts)ModalComputer scienceHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

This paper is concerned with a cross-cultural study of modality expressions in asking for permission by Vietnamese and English speakers. The study involved 209 Canadian and Vietnamese informants with the use of a Discourse Completion Task questionnaire. A total of 3000 utterances were chosen for analysis to gain insights into the frequency and types of lexico-modal markers manifested in the two languages. It is found that hearer-oriented verbal style tends to be dominant in Vietnamese while the speaker-oriented strategy is more favored in English. Vietnamese speakers tend to employ direct strategies with a dominant use of appealers which sounds intimate to the hearer. English speakers, by contrast, incline to conventionally-indirect strategies such as Can I, Could I, etc. It is also evident that Vietnamese speakers frequently use politeness markers when they communicate with the older, but they hardly use them for their peers. English speakers, however, use politeness markers for all partners with a slight variation. Another noteworthy similarity is that both Canadian and Vietnamese women modalize their language than men.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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 head0.119
GPT teacher head0.465
Teacher spread0.346 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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