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Record W3133210779 · doi:10.1177/1028315321990745

Internationalization of Chinese Higher Education: Is It Westernization?

2021· article· en· W3133210779 on OpenAlexaff
Yan Guo, Shibao Guo, Lorin G. Yochim, Xiaoli Liu

Bibliographic record

VenueJournal of Studies in International Education · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsConcordia University of EdmontonUniversity of Calgary
Fundersnot available
KeywordsInternationalizationWesternizationInternationalization of Higher EducationCurriculumChinaHigher educationPolitical scienceSociologyInternational educationIndigenousPedagogyPublic relationsBusinessModernization theoryInternational trade

Abstract

fetched live from OpenAlex

Internationalization has become a strategic policy priority for many Chinese higher education in the process of becoming world-class universities. However, there is little research focusing on students’ experiences of internationalization at home. This research investigates how Chinese undergraduates interpreted and experienced internationalization at a prestigious university in China. Data for the study were collected through policy document analysis, semi-structured interviews with students, and site visits. The results of the study reveal that students perceive internationalization as Westernization, question the prominence of English in the university’s internationalization in both formal and informal curricula, and raise concerns about unequal access to internationalization. The study interrogates the unidirectional orientation of internationalization between China and the developed Western world. It calls for an approach to the de-Westernization of internationalization, reclaiming indigenous Chinese epistemology, language, and culture. The findings have important implications for an alternative social imaginary of internationalization for researchers and policymakers.

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)0.002
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 score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.010
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0000.001
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 head0.069
GPT teacher head0.396
Teacher spread0.327 · 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

Citations115
Published2021
Admission routes1
Has abstractyes

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