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Record W3117997502 · doi:10.1163/25902539-02040009

Fostering Global Citizenship through Student Mobility: <i>COVID-19 and the 4th Wave in Internationalization of Education</i>

2020· article· en· W3117997502 on OpenAlexaff
Ratna Ghosh

Bibliographic record

VenueBeijing international review of education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsMcGill University
Fundersnot available
KeywordsCitizenshipContext (archaeology)GoodwillGlobal citizenshipPolitical scienceStudy abroadInternational educationImmigrationHigher educationInternational tradeEconomic growthBusinessEconomicsPoliticsGeographyLaw

Abstract

fetched live from OpenAlex

Although the phenomenon of student mobility can be traced back to over a thousand years, a remarkable increase began from 1995 when the World Trade Organization released the General Agreement on Trade in Services, making higher education a tradable commodity. International mobility programs have the potential to provide the environment for global citizenship by empowering students to be resilient and become citizens of the world. Higher education institutions are clamoring to prepare students for living in highly diverse societies, and countries use the soft power of international exchanges to develop goodwill. However, the striking increase in student mobility has suddenly come to a dramatic halt in recent months globally due to the COVID-19 pandemic, and the impact on international students has been most severe. In this context, this paper briefly discusses the evolution of student mobility and how it fosters global citizenship.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0020.002
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 head0.099
GPT teacher head0.454
Teacher spread0.356 · 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
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

Citations14
Published2020
Admission routes1
Has abstractyes

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