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Record W4206956088 · doi:10.26522/ssj.v16i1.2685

Towards a More Just Canadian Education-migration System: International Student Mobility in Crisis

2022· article· en· W4206956088 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueStudies in Social Justice · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmigrationSocial justiceEconomic JusticePolitical scienceSocial mobilityPerspective (graphical)SociologyCoronavirus disease 2019 (COVID-19)Political economyLaw

Abstract

fetched live from OpenAlex

Education-migration, or the multi-step recruitment and retention of international students as immigrants, is an increasingly important component of both higher education and so-called highly-skilled migration. This is particularly true in Canada, a country portrayed as a model for highly-skilled migration and supportive of international student mobility. However, education-migration remains under-analyzed from a social justice perspective. Using a mobility justice framework, this paper considers COVID-19’s impact on Canada’s education-migration system at four scales: individuals, education institutions, state immigration regimes, and planetary geoecologies. It identifies ethical tensions inherent to Canada’s education-migration from a systems-level and suggests that a multi-scalar approach to social justice can both usefully complexify discussions and introduce unsettling paradoxes. It also stresses that the COVID-19 pandemic offers an opportunity to reimagine rather than return.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.531
Teacher spread0.441 · 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