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Record W3113455418 · doi:10.1163/25902539-02040011

Internationalization as a Moral Project: <i>An Exploration of the Emotions, Deliberations, and Concerns of Teaching Faculty</i>

2020· article· en· W3113455418 on OpenAlexaff
Laura Servage, Lorin G. Yochim

Bibliographic record

VenueBeijing international review of education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsUniversity of AlbertaConcordia University of Edmonton
Fundersnot available
KeywordsInternationalizationSociologyWork (physics)PedagogyEngineering ethicsMoral dilemmaEpistemologyPolitical sciencePsychologySocial psychologyEngineeringBusinessPhilosophy

Abstract

fetched live from OpenAlex

This article discusses the perspectives of teaching faculty on the growing number of international students in their undergraduate classrooms. Our analysis takes note of expressions of emotion in faculty accounts and uses these to draw attention to the careful deliberations by which faculty reconcile personal commitments with the changing conditions of their work. We highlight moral and epistemological tensions in the project of internationalizing higher education. While these tensions have been considered for some time in critical comparative education circles, they are rarely acknowledged at the level of the mundane, daily practices of teaching. Our findings lead us to propose an alternative figuring of internationalization as a moral project. We believe that shifting the discussion toward moral tensions embedded in the lived reality of the contemporary university provides a rich ground for resolving any number of vexing dilemmas and, perhaps, to realizing the promise of internationalization.

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)0.009
metaresearch head score (Gemma)0.008
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 score0.015
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.038
Scholarly communication0.0150.009
Open science0.0010.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.107
GPT teacher head0.449
Teacher spread0.341 · 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
Published2020
Admission routes1
Has abstractyes

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