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Record W2560036180 · doi:10.5539/elt.v10n1p18

Study of Motives of Chinese Business English Development Based on the Theory of Human Capital

2016· article· en· W2560036180 on OpenAlexvenueno aff
Ouyang Meichang, Wenzhong Zhu, Dan Liŭ

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
FundersGuangdong University of Foreign Studies
KeywordsBusiness EnglishBachelorHuman capitalFoundation (evidence)Perspective (graphical)Social capitalPsychologyChinaSet (abstract data type)Bachelor degreeDisciplineCapital (architecture)SociologyManagementPedagogyMathematics educationSocial sciencePolitical scienceEconomicsEconomic growthComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Business English in China has evolved into a cross-disciplinary program from ESP, with more than 1000 universities having set the program of business English in bachelor, master or doctor degree levels. In general, it has undergone a rapid development and enjoyed a more and more social recognition. This paper tries to uncover the underlying motives of the quick development of the program based on the perspective of human capital theory, and find out the possible relationship between business English teaching development and human capital The results conclude that there exists the relationship between them, and the theory of human capital opens a novel theoretical foundation for the related researches.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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)0.0010.000

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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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 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

Citations4
Published2016
Admission routes1
Has abstractyes

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