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Record W4415388437 · doi:10.5539/hes.v15n4p377

Language Ability, Social Demand, and Employment Policies: A Comparative Study of Chinese and Thai International Students’ Employability

2025· article· W4415388437 on OpenAlexvenueno aff
Penpisut Sikakaew

Bibliographic record

VenueHigher Education Studies · 2025
Typearticle
Language
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityChinaIncentiveLanguage proficiencyWork (physics)International educationCareer developmentHigher educationLanguage barrier

Abstract

fetched live from OpenAlex

This study explores the factors shaping the employability of international students by comparing Chinese students in Thailand and Thai students in China. Focusing on three dimensions—language proficiency, social demand, and employment policies. The research employs a questionnaire survey, with 390 valid responses. Data was analyzed using independent-sample t-tests and multiple linear regression. The findings indicate that language proficiency is the decisive factor shaping graduates’ career planning, adaptability, and competitiveness, while social demand—encompassing family expectations, labor market conditions, and cultural norms—further directs career choices and entrepreneurial intentions, whereas employment policies related to visas, work permits, and incentives exert only limited influence due to low awareness and implementation barriers. The findings suggest that universities should strengthen career-oriented language training and guidance services, while policymakers in China and Thailand should prioritize clearer communication and practical alignment of policies with labor market needs to enhance international student employability.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.052
GPT teacher head0.422
Teacher spread0.370 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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