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Record W2900599461 · doi:10.5430/elr.v7n4p1

The Lexicalization Patterns of Manner Motion Events in Vietnamese

2018· article· en· W2900599461 on OpenAlexvenueno aff
Luu Quy Khuong, Ly Ngoc Toan

Bibliographic record

VenueEnglish Linguistics Research · 2018
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsnot available
Fundersnot available
KeywordsLexicalizationVietnameseMotion (physics)LinguisticsExperiential learningFoundation (evidence)PsychologyLexical itemComputer scienceMathematics educationArtificial intelligenceHistoryPhilosophyArchaeology

Abstract

fetched live from OpenAlex

The purpose of this paper is to illustrate how Vietnamese students lexicalize or express in words the idea of motion. This study was conducted on the traditional foundation of Talmy’s (1985) lexicalization patterns. This theory involved in the way of people’s experience is rendered into languages via the semantic content of lexical items to express experiential categories. The data were derived from the analysis of the writings of fifty 12th- graders and fifty 6th- graders at Phu Rieng secondary school, Binh Phuoc province, Vietnam about the picture story “Frog where you” are by Mayer (2003). The results of the research provided insights into how Vietnamese speakers express the experience of motion in their language. These results suggest that there are considerable differences between Vietnamese and some other languages in the accounts of motion events.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.057
GPT teacher head0.421
Teacher spread0.365 · 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 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
Published2018
Admission routes1
Has abstractyes

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