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Record W2974615374 · doi:10.11575/prism/37061

Understanding how International Graduate Students in Canada Reconstruct their Writing Identities

2019· dissertation· en· W2974615374 on OpenAlexaboutno aff
Wan Ying

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPedagogyLibrary scienceSociologyPsychologyComputer science

Abstract

fetched live from OpenAlex

This study was designed to explore the reconstruction of writing identity of international students in Canada. This study was conducted based on the concepts of writing identity proposed by Ivanič, who classified writing identity as autobiographical self, discoursal self, self as author and possibilities for self-hood, to inform that writing identity is (re)constructed in the light of various influential factors. The data were collected from interviews and journals of four Chinese international graduate students from the University of Calgary regarding their intercultural perceptions and experiences of writing. Results indicated that the process of reconstruction of writing identity is fluid. Participants transformed their positionings as English academic writers in relation to the following impacts: (1) different disciplines and requirement of writing; (2) previous experiences; (3) ambient environment; and (4) discourse. In order to fit into the new academic discourse, some of the participants developed their L1 writing identity to a L2 writing identity, while some of them reconciled L1 and L2 writing identity to a hybrid identity or a shifted identity. The implications of this study revealed the importance of teaching international students with conventions of academic writing, and helping them change the Chinese way of writing and thinking since writing is likewise an interacting between their written texts and thoughts. Meanwhile, the discipline-specific workshops and courses were found useful in facilitating international students’ improvement on writing performance and (re)construction of their writing identity as English academic writers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.178
GPT teacher head0.340
Teacher spread0.161 · 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 teacher head, not a consensus.

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
Published2019
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicDiscourse Analysis in Language StudiesFrench-language works237,207