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Record W3120810749 · doi:10.47678/cjhe.vi0.188777

Power, Politics, and Education: Canadian Universities and International Education in an Era of New Geopolitics

2021· article· en· W3120810749 on OpenAlexaffvenueabout
Roopa Desai Trilokekar, Amira El Masri, Hani El Masry

Bibliographic record

VenueCanadian Journal of Higher Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversité de MontréalUniversité LavalYork UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsGeopoliticsSoft powerPoliticsChinaProsperityForeign policyGovernment (linguistics)National securityPolitical scienceContext (archaeology)Power (physics)Public administrationSociologyHigher educationEconomic growthPolitical economyLawEconomicsGeography

Abstract

fetched live from OpenAlex

This paper focuses on the recent political spars between Canada and Saudi Arabia as well as China and their impact on Canadian universities. It asks three questions: (1) What key issues did Canada’s political strains with Saudi Arabia and China raise for Canadian universities’ international education (IE) initiatives and what issues were absent? (2) What do these key issues suggest about Canada’s approaches to IE in an era of new geopolitics? and (3) What implications can be drawn from these cases about Canadian university-government relations in the context of new geopolitics? Given the powerful role media plays in education policy, a systematic study was conducted across three main media sources to identify 74 articles and news releases between August 2018 and November 2019. Three dominant themes are identified and analyzed, each vividly illustrating the close ties between global politics, government foreign policy and IE within Canadian Universities. On the one hand, the narratives speak to concerns about IE as a risk to national security and, on the other, as a vehicle for Canada’s economic prosperity. However, what the media has not achieved is a broader discussion on how Canada needs to revisit its IE objectives and approaches in light of broader geopolitical shifts. Using the theoretical framework of soft power, the paper speaks to the limitations and short-sightedness of Canada’s approach to IE as soft power in this era of new geopolitics and concludes with three recommendations for Canada.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.317
Teacher spread0.301 · 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.

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

Citations9
Published2021
Admission routes3
Has abstractyes

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