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Record W6959534252 · doi:10.11575/prism/49009

Chinese Student Newcomers’ Transition to a Canadian Postsecondary EAP Program: Pre- and Post-Departure Comparison

2021· other· en· W6959534252 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2021
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsBiculturalismAcculturationNormativeTransculturationTransition (genetics)Neuroscience of multilingualismLanguage proficiencyCultural diversityHigher education

Abstract

fetched live from OpenAlex

The study investigates the cultural and linguistic lived experiences of Chinese international student newcomers in a Canadian postsecondary English for Academic Proposes (EAP) program and whether or not intercultural transformations occur in English learning. As Chinese English learners are immersed in the Canadian tertiary education settings, their normative assumptions about knowledge will be challenged. However, they have experienced an integration by applying different biculturalism strategies, which is characterized by selective acculturation (Schwartz, Ángel Cano, & Zamboanga, 2015). In this study, Chinese-dominant biculturalism marks a simultaneous response to the host culture when participants have limited English proficiency and little contact with the Canadian larger society; while Canadian-dominant biculturalism contains a fluctuate psychological adjustment of loss-transformation-reclamation after participants experienced marginalization. This article aims to delineate Chinese students’ transition trajectories for home and host educational authorities to understand and provide pre-departure and post-departure support to the Chinese students as they will complete their studies internationally.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicPlant Pathogens and ResistanceFrench-language works237,207