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Record W4396871901 · doi:10.1080/17450101.2024.2350533

International students’ cultural engagement through constructing distance or proximity

2024· article· en· W4396871901 on OpenAlexaffabout
Anne-Cécile Delaisse, Gaoheng Zhang

Bibliographic record

VenueMobilities · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSociologyPsychologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

International students’ contact and engagement with various cultures has received increased scholarly attention. This scholarship tends to either celebrate students’ cosmopolitanism or highlight their difficulties ‘adapting’ in their receiving countries. In this paper, we examine students’ own perceptions of and engagement with their sending and receiving countries’ cultures through the dialectic of distance and proximity, gleaned from mobilities studies. Based on 20 in-depth online interviews with Vietnamese nationals studying in Vancouver and Paris, our analysis highlights how these students construct or deconstruct notions of distance and proximity between Vietnam and their receiving countries (i.e. France and Canada), as well as between themselves and each of these countries. First, we examine how, before their departure, students cultivate a sense of cultural proximity to their geographically distant countries of destination, through studying and consuming media in French or English. Second, we address students’ rapport with French and Canadian societies as well as their sense of proximity to or distance from Vietnamese culture while studying in France and Canada. We examine how these (de-)constructions of distance can be related to students’ cosmopolitanism. We argue that notions of distance and proximity help foster a nuanced understanding of international students’ mobilities and cosmopolitanism.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.012
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0120.005
Open science0.0010.010
Research integrity0.0010.002
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 head0.073
GPT teacher head0.421
Teacher spread0.348 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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