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Record W3045856179 · doi:10.32674/jis.v10i2.961

Geographic Embeddedness of Higher Education Institutions in the Migration Policy Domain

2020· article· en· W3045856179 on OpenAlexaffabout
Alexandra M. Bozheva

Bibliographic record

VenueJournal of International Students · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsWestern University
Fundersnot available
KeywordsEmbeddednessImmigrationHigher educationCorporate governanceImmigration policyHigher education policyInternational educationPolitical scienceState (computer science)Enrollment managementPublic relationsPublic administrationEconomic growthEducation policySociologyManagementSocial scienceLawEconomics

Abstract

fetched live from OpenAlex

In 2014, Canada issued its first International Education Strategy, articulating targets for international enrollment and its economic benefits, but lacking international student retention goals. Universities and colleges used to be places where students could get immigration advice, but past Bill C-35 only Regulated Canadian Immigration Consultants can provide such advice. There is no requirement for institutions to hire these consultants. I investigate the geographic stretch of the education domain’s engagement with retention, through an examination of immigration advising support provision across Canada’s campuses. This provision is highly uneven, with a moderate association with school size, reflecting the voluntary nature of such engagement. A defined international student retention strategy could possibly change the current state of immigration governance through the education domain.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.007
Scholarly communication0.0070.003
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.033
GPT teacher head0.428
Teacher spread0.395 · 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 designObservational
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

Citations4
Published2020
Admission routes2
Has abstractyes

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