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Record W4361275287 · doi:10.5430/wjel.v13n5p231

The Expressions of Epistemic Modality in English and Vietnamese: A Contrastive on “thấy” and “nghĩ” in Vietnamese and Mental Verbs in English

2023· article· en· W4361275287 on OpenAlexvenueno aff
Han Van Ho

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsEpistemic modalityPropositionModality (human–computer interaction)Objectivity (philosophy)LinguisticsVocabularyVietnameseExpression (computer science)Value (mathematics)PsychologyComputer scienceEpistemologyPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Epistemic modality is described as the speaker's judgment, assessing the degree of the factual proposition, or the speaker's confidence or non-confidence in the truth value of the proposition. The paper focuses on the expression of “thấy”, “nghĩ” predicates in Vietnamese and compares with mental verbs in English. To achieve the research objectives, the paper uses descriptive, statistical and comparative methods to clarify modality in general and epistemic modality in particular. The paper initially contributes to clarifying the definition, category, and identification of epistemic modality in terms of grammar and vocabulary. Next, the paper points out the similarities and differences in the expression of epistemic modality in English and Vietnamese. The results show that the nature of vocabulary and syntax basically exists value of factuality and non-factuality. The most important feature of epistemic modality is subjectivity and objectivity. The speaker "I/Tôi" clearly expresses or implies commitment for what is said. Understanding and applying modality in general and epistemic modality in particular will help learners acquire language and culture better in the process of communication and translation.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.256
Teacher spread0.244 · 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 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
Published2023
Admission routes1
Has abstractyes

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