MétaCan
Menu
Back to cohort
Record W3043664733 · doi:10.1177/2347631120930538

Internationalization in Canadian Higher Education Institutions: Ontario

2020· article· en· W3043664733 on OpenAlexaboutno aff
Ali Khorsandi Taskoh

Bibliographic record

VenueHigher Education for the Future · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationMultinational corporationContext (archaeology)Political scienceCurriculumRealmInternationalization of Higher EducationHigher educationInternational educationPoliticsPublic relationsPublic policyPublic administrationEconomic growthBusinessEconomicsInternational trade

Abstract

fetched live from OpenAlex

Education is a tool for collaboration among nations. The emergence of concepts as internationalization of educational policies, students-staff exchange programs, internationalization of curriculum, internationalization at home (IAH) or even the emergence of multinational agencies to expedite global exchanges in the realm of Higher Education lead educational policy-makers to confess that segregation of the educational policies from nations’ foreign affairs policies have no promising results than failure of the nations’ educational goals and priorities. Based on the qualitative and case study research methodologies, we adopted critical policy analysis (CPA) to address the question of “why does a Canadian public university engage in internationalization?”. The study showed that the decision to acknowledge internationalization as a priority at a public university in Ontario is based upon different motives ranging from commercial-economic and socio-political to academic-educational and profile-building components. The study also identified the gradual extension of market-based rationales that have historically been absent from traditional university policies in the Canadian context to educational initiatives and academic rationales.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.331
Teacher spread0.295 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueHigher Education for the FutureSame topicHigher Education Governance and DevelopmentFrench-language works237,207