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Record W2997237717 · doi:10.14507/epaa.28.4609

The political process of international education: Complementarities and clashes in the Manitoba K-12 sector through a multi-level governance lens

2020· article· en· W2997237717 on OpenAlexaffabout
Merli Tamtik, Angela O’Brien-Klewchuk

Bibliographic record

VenueEducation Policy Analysis Archives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsStakeholderPoliticsPublic administrationIdeologyCorporate governanceContext (archaeology)CurriculumGovernment (linguistics)Political scienceSociologyPublic relationsEconomicsEconomic growthManagementLaw

Abstract

fetched live from OpenAlex

International education has become a policy sector of growing importance to Canada. With increased government regulations, disconnect is often observed between the intended policy outcomes and practice. This study aims to explain this disconnect by analyzing the heterogeneity among stakeholder interests. It focuses on 1) distribution of authority; 2) heterogeneity of values; and 3) complementarities and clashes in policy issues. A multi-level governance (MLG) framework (Chou et. al., 2017; Hooghe & Marks, 2003), as a guiding theoretical lens, is applied to examine the interactions among governments (federal-provincial), non-governmental organizations, school administrators, international students and their families in the context of the Manitoba K-12 sector. Data for this study were collected through document analysis and 40 semi-structured interviews. Findings indicate increased steering power of both the federal and provincial governments to regulate international education with conflicting agendas based on political ideologies. The pursuit of Canada’s economic competitiveness through K-12 international education has led to a rise in the authority of non-governmental actors, including parents and students, to shape the services, programs and curriculum content offered by public schools. The study proposes adding an additional layer to the MLG framework, that of the complexities within stakeholder groups.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

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

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 head0.118
GPT teacher head0.416
Teacher spread0.298 · 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 designQualitative
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

Citations8
Published2020
Admission routes2
Has abstractyes

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