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Record W4402723198 · doi:10.1002/psp.2832

Transnational lives interrupted: The Canadian state and Indian international student experiences during the COVID‐19 pandemic

2024· article· en· W4402723198 on OpenAlexaffabout
Neil Amber Judge, Margaret Walton‐Roberts

Bibliographic record

VenuePopulation Space and Place · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)State (computer science)State of exceptionPolitical scienceSociologyEconomic growthGeographyVirologyMedicineLawPoliticsEconomicsOutbreakComputer science

Abstract

fetched live from OpenAlex

Abstract Canada has emerged as a major education destination for international students from across the world. International students are understood to significantly contribute towards the labour market and economic growth of Canada including the higher education sector that has come to financially rely on international students. India has emerged as the largest source of international students to Canada in recent years making them a significant category of migrants impacted by the covid‐19 pandemic and the subsequent lockdown measures implemented by the Canadian state. This paper looks at the experiences of Indian international students already in Canada and prospective students in India planning to pursue their studies in Canada. The pandemic delayed international education plans for many students in India while causing significant disruption to the studies, employment, and living arrangements of international students in Canada. Such disruptions created considerable uncertainty over their financial situation including meeting various eligibility requirements for work permit after graduation. This paper reveals the deeply embodied and personalised consequences for students in the face of state responses to balancing pandemic control and retaining financial and economic contribution during the pandemic.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.739
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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