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Record W3008925899 · doi:10.1111/weng.12458

Translingual practices at a Shanghai university

2020· article· en· W3008925899 on OpenAlexaff
Yang Song, Angel M. Y. Lin

Bibliographic record

VenueWorld Englishes · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsInternationalizationEnglish as a lingua francaContext (archaeology)SociologyInternationalization of Higher EducationNegotiationPedagogyLingua francaIntercultural communicationDisciplineMetropolitan areaMeaning (existential)EthnographyInterculturalityScope (computer science)Intercultural learningLinguisticsPsychologySocial scienceAnthropologyGeography

Abstract

fetched live from OpenAlex

Abstract The present study examines translingual practices among students enrolled in international English‐medium instruction (EMI) Master's degree programmes in a top‐rated comprehensive university in Shanghai, China. Ethnographic observations across urban/institutional spaces and social media as well as in‐depth student interviews converge to reveal that while English has been used as a lingua franca for disciplinary teaching, learning, and navigation of everyday life, students have been engaged in translingual practices (1) to understand and create meaning out of intercultural experiences in the cosmopolitan city of Shanghai, and (2) to negotiate epistemic frameworks as contextualized in both the institutional student management setting and the global politics of discipline‐specific knowledge production. This article is hence aimed at expanding the scope of translingual research to include critical inquiry into the role of English as a lingua franca in students’ transcultural/trans‐epistemic experiences in EMI programmes in the context of internationalization 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)0.001
metaresearch head score (Gemma)0.001
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 score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.057
GPT teacher head0.223
Teacher spread0.166 · 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

Citations32
Published2020
Admission routes1
Has abstractyes

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