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Record W4385562828 · doi:10.32674/jcihe.v15i3.4688

COVID-19 Experiences of International Students in Vancouver, British Columbia, Canada

2023· article· en· W4385562828 on OpenAlexaboutno aff
Ajay Garg, Raymundo Rosada, Jay Ariken

Bibliographic record

VenueJournal of Comparative & International Higher Education · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicNationalityCoronavirus disease 2019 (COVID-19)AccommodationTest (biology)HygienePsychologyPerception2019-20 coronavirus outbreakImmigrationPolitical scienceMedicineInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

This study looked into the lived experiences of international students during the COVID-19 pandemic in Vancouver, British Columbia, Canada. The research focused on how international students viewed the COVID-19 pandemic, their personal, social, economic, health and hygiene, and schooling experiences. A validated and reliable researchers-made questionnaire was used. Weighted means and Fisher’s Exact Hypothesis Testing on Association were used to analyze the responses of the international students. The researchers used Fisher’s exact test since they wanted to know whether the proportions for one variable were different among values of the other variable. Foreign students had a solid grasp of the potential risks COVID-19 posed and accepted the associated lockdown requirements. The survey results indicated that the students’ nationality played a vital role in their perception of their financial health and well-being. Students were insecure with their accommodation, expenses, and scheduling. Lastly, they also felt alone, and economically challenged.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.359
Teacher spread0.302 · 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.

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
Published2023
Admission routes1
Has abstractyes

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