MétaCan
Menu
Back to cohort
Record W4385480003 · doi:10.25071/28169344.33

Understanding Chinese International Students' Struggle in Canadian University during COVID-19: A Literature Review

2023· review· en· W4385480003 on OpenAlexaffabout
Chunlei Liu

Bibliographic record

VenueYU-WRITE Journal of Graduate Student Research in Education · 2023
Typereview
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsYork University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)ChinaGovernment (linguistics)ImmigrationFace (sociological concept)Political science2019-20 coronavirus outbreakEconomic growthPsychological resilienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)International educationHigher educationSociologyPsychologyOutbreakMedicineSocial scienceEconomicsLaw

Abstract

fetched live from OpenAlex

The economic impact of international students in Canada is tremendous. As the enrollment of domestic students has decreased, the admission of overseas students has made up for the financial losses that Canadian institutions suffer due to the drop in domestic student enrollment. China is a significant exporter of international students to Canada, sending a sizable number of them there yearly. Chinese international students' entrance to Canadian universities is being impacted by the COVID-19 pandemic. This article contends that because of their temporary immigration status, international students in Canada are at risk. It does this by drawing on the literature analysis approach. They are not included in the majority of government assistance initiatives intended to assist Canadians during this outbreak. The majority of overseas students struggle financially and psychologically as a result of the pandemic. The circumstance is causing a further drop in the admittance of international students, with economic repercussions for Canadian institutions. The report advances our knowledge of the struggles faced by international students and educational institutions during the COVID-19 pandemic by examining the issues they face as well as the methods needed to increase their resilience and universities' capacity.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.749
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.337
GPT teacher head0.556
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueYU-WRITE Journal of Graduate Student Research in EducationSame topicHigher Education Governance and DevelopmentFrench-language works237,207