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Record W4416735960 · doi:10.1080/15562948.2025.2588153

Privilege and Precarity: Migration Journeys of Former International Students in Canada Through the Lens of the Aspirations and Capabilities Framework

2025· article· en· W4416735960 on OpenAlexafffundabout
Dominik Formanowicz, Tingting Zhang, Rupa Banerjee, Rezwana Ahmed, Isaac Garcia-Sitton

Bibliographic record

VenueJournal of Immigrant & Refugee Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsToronto Metropolitan UniversityYork University
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsPrivilege (computing)Lens (geology)Through-the-lens meteringImmigrationRefugee

Abstract

fetched live from OpenAlex

International student enrolment has surged globally, transforming higher education systems worldwide. In Canada, this growth has not only transformed post-secondary institutions but also recalibrated the immigration system, with international students positioned as prime candidates for permanent residency after graduation. Against this backdrop, this study investigates how former international students (FIS) graduating from publicly funded Canadian universities navigate migration decisions. Using a grounded theory approach, it explores how privilege and precarity shape the aspirations and capabilities of FIS, influencing their migration experiences. Findings question Canada’s image as an unequivocally attractive destination, emphasizing the evolving, situational aspects of migration choices. Systemic barriers, including employment challenges and inconsistent policies, complicate desires to stay. We underscore the need for integrated policies connecting education, immigration, and labour markets and offer recommendations to retain and integrate international student talent.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.031
GPT teacher head0.344
Teacher spread0.313 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

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