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Record W18898646 · doi:10.5206/cie-eci.v43i3.9261

International Students as ‘Ideal Immigrants’ in Canada: A disconnect between policy makers’ assumptions and the lived experiences of international students

2015· article· en· W18898646 on OpenAlexaffvenueabout
Colin Scott, Saba Safdar, Roopa Desai Trilokekar, Amira El Masri

Bibliographic record

VenueComparative and International Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsYork UniversityUniversity of Guelph
Fundersnot available
KeywordsProsperityGraduation (instrument)ImmigrationGovernment (linguistics)Work (physics)Political scienceInternational educationThematic analysisImmigration policyHigher educationPublic relationsEconomic growthEconomicsSociologyQualitative researchSocial science

Abstract

fetched live from OpenAlex

Recent policy changes in Canada highlight the strategic role International Students (IS) in the country’s economic development and future prosperity. With the release of Canada’s first international education strategy, the federal government has intimately tied international education to the domestic economy by attracting and retaining skilled workers to prepare Canada for the global market place. IS are particularly desirable candidates for permanent residency because their Canadian credentials, proficiency in at least one official language, and their relevant Canadian work experience is assumed to allow them to integrate more easily into the labour force upon graduation. Through 11 focus groups with 48 IS from two post-secondary institutions in the province of Ontario, we explored the adjustment of IS as they adapt to Canada and transition from student to worker. Thematic analysis suggests a disconnect between policy makers’ assumptions and the lived experiences of IS in Canada. Specifically, we find that IS’ integration into Canadian society into the domestic labour market is hindered by adjustment difficulties pertaining to language abilities, poor connectedness to host communities, and perceived employer discrimination against IS. We offer policy recommendations for how international education can better prepare IS for the Canadian labour market.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.699

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0460.030
Scholarly communication0.0140.004
Open science0.0030.011
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.129
GPT teacher head0.466
Teacher spread0.337 · 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 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

Citations130
Published2015
Admission routes3
Has abstractyes

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