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Record W2475448511 · doi:10.1177/0896920516654554

Canada and the Global Rush for International Students: Reifying a Neo-Imperial Order of Western Dominance in the Knowledge Economy Era

2016· article· en· W2475448511 on OpenAlexaffabout
Marjorie Johnstone, Eunjung Lee

Bibliographic record

VenueCritical Sociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsDominance (genetics)GlobalizationGlobal governanceKnowledge economyImmigrationGlobal educationInternational educationPolitical economyPolitical scienceCorporate governanceEducation policyPower (physics)EconomySociologyEconomicsHigher educationEconomic growthLawManagement

Abstract

fetched live from OpenAlex

In a global knowledge economy, western nations compete for the best knowledge workers, while positioning English language and western education as superior. Drawing from critical theories of globalization, we argue that the international education field has become a site to maintain a neo-imperial agenda concealed by a neoliberal rhetoric of progress and economic expediency. Using Canada as a case study, we critically examine the global tactics of power and governance strategies in international education policy, as they influence and shape education and immigration policy within Canada. We illustrate how the OECD positions itself for global dominance in education and (re)produces the international education field using tactics such as rescaling, the policy cycle and ‘self-responsibilizing’ students. This process creates and maintains a global market for knowledge producers and expands the soft power of western nations.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.888
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0240.060
Scholarly communication0.0140.004
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.384
Teacher spread0.367 · 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

Citations29
Published2016
Admission routes2
Has abstractyes

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