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Record W2802837368

Transcultural university experiences: illuminating the influence of internationalization on relationships between staff and students

2017· article· en· W2802837368 on OpenAlexaffabout
Chelsey Laird, Camila Miranda

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsInternationalizationSociologyInstrumentalismProcess (computing)IdeologyHigher educationQualitative researchIdealismPedagogyPolitical scienceSocial scienceEpistemologyBusiness
DOInot available

Abstract

fetched live from OpenAlex

T he process of internationalization has created a new landscape for higher education discussions: the transcultural university (Baker, 2016), where multiple languages and cultures coexist. Ideological assumptions behind the process of internationalization, such as idealism, instrumentalism, and educationalist (Stier, 2004) reveal various ways different stakeholders may engage with the process of internationalization. Our paper will draw on qualitative data from a SSHRC-funded study on critical internationalization at a Western Canadian university to illuminate the relationships between students, both domestic and international, and staff. Beck (2012) points to the gap in literature that addresses the perspectives and understandings of participants involved in internationalization, and little is known about how students and staff experience internationalization in their interactions with each other.

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)0.013
metaresearch head score (Gemma)0.018
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 score0.036
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0290.035
Scholarly communication0.0150.009
Open science0.0020.018
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.070
GPT teacher head0.342
Teacher spread0.272 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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