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Record W1706670143 · doi:10.18806/tesl.v20i1.937

Japanese Exchange Students' Writing Experiences in a Canadian University

2002· article· en· W1706670143 on OpenAlexfundvenueaboutno aff
Ling Shi, Gulbahar H. Beckett

Bibliographic record

VenueTESL Canada Journal · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of Cincinnati
KeywordsTask (project management)PsychologyNarrativeStyle (visual arts)RhetoricAcademic writingCredibilityWriting styleLinguisticsPerceptionPedagogySecond language writingMathematics educationSecond languageLiteraturePolitical scienceArt

Abstract

fetched live from OpenAlex

This study investigated the learning experiences of 23 Japanese students in a one-year Academic Exchange Program at a Canadian university. The participants wrote either an opinion task or a summary task at the beginning of the program using two preselected source texts. They then revised the drafts at the end of the program and were interviewed to comment on what they had learned about English writing during their study in Canada. Analyses of the interview data and comparisons of the original and the revised texts indicate that participants revised their drafts to use more words of their own and to follow the more direct English style and linear rhetoric pattern. The narrative of how these students adopted English writing conventions and their perceptions of whether they would continue to use them when they returned to Japan suggests an impact of English training not only on their English but also on their Japanese academic writing.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.478
Threshold uncertainty score0.961

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0260.005
Scholarly communication0.0080.002
Open science0.0020.007
Research integrity0.0020.003
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 head0.024
GPT teacher head0.228
Teacher spread0.204 · 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

Citations17
Published2002
Admission routes3
Has abstractyes

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Same venueTESL Canada JournalSame topicDiscourse Analysis in Language StudiesFrench-language works237,207