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Multilingual International Students From the Perspective of Faculty

2021· book-chapter· en· W4200405207 on OpenAlexaffabout
Vander Tavares

Bibliographic record

VenueIGI Global eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsYork University
Fundersnot available
KeywordsInternationalizationPerspective (graphical)PerceptionDiversity (politics)International educationCultural diversityPedagogyMedical educationPsychologyHigher educationSociologyLibrary sciencePolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

This chapter explores the experiences and perceptions of 14 faculty members toward multilingual international students at River University—a large, research-focused university in Ontario. Data was collected through an online survey and analysed thematically. Responses were categorised under three broad categories with respect to faculty's (1) perceptions of multilingual international students' contributions to River's academic community, (2) challenges surrounding faculty's interactions with multilingual international students, and (3) strategies developed and implemented to support students' academic success. Overall, findings were consistent with those in the current research literature, in which language proficiency was identified by faculty as a major concern, and multilingual international students were considered important for the enhancement of cultural and intellectual diversity, and for the internationalisation of higher education.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.008
Scholarly communication0.0100.004
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.053
GPT teacher head0.383
Teacher spread0.330 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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