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Record W4385481180 · doi:10.25071/28169344.17

Let's Talk About Decolonial Internationalization

2023· article· en· W4385481180 on OpenAlexafffundabout
Ezgi Ozyonum

Bibliographic record

VenueYU-WRITE Journal of Graduate Student Research in Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsConcordia University
FundersConcordia UniversityGovernment of Canada
KeywordsInternationalizationHigher educationInternationalization of Higher EducationHierarchyPolitical scienceSociologyOrder (exchange)Quality (philosophy)Global educationPosition (finance)Public relationsPedagogyBusinessInternational trade

Abstract

fetched live from OpenAlex

There is increasing pressure on higher education institutions (HEIs) to adopt internationalization strategies. The phenomenon of internationalization of higher education is described as “the intentional process of integrating an international, intercultural or global dimension into the purpose, functions and delivery of post-secondary education, in order to enhance the quality of education and research for all students and staff, and to make a meaningful contribution to society” (De Wit et al., 2015, p.281). In higher education, we face a central problem. While universities promote internationalization strategies, they spread Eurocentric ways of knowing, standards, and norms as global. International mobility is predominantly a student and faculty movement from the East to the West. This mobility disseminates the colonial global educational engagement where the West seems to be the ultimate knowledge producer. The challenge of HEIs is to interrupt the colonial patterns in international education. This position paper examines the hierarchy of knowledge production in higher education through a decolonizing framework. Subsequently, it proposes a decolonial internationalization in the case of Canadian Universities.

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)0.004
metaresearch head score (Gemma)0.007
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.159
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0140.045
Scholarly communication0.0120.016
Open science0.0010.007
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0080.001

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 head0.249
GPT teacher head0.565
Teacher spread0.316 · 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
GenreCommentary

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
Published2023
Admission routes3
Has abstractyes

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