Bibliographic record
Abstract
Studies investigating cultural influences on second-language writing have been mainly product-oriented. Moreover, research on writing processes has mostly focused on the strategies of writing and learning to write. Writing processes where we can see the evolution of the writer's identity and beliefs have been less adequately addressed. Therefore, this article focuses on the dynamic relationship of culture, identity, and beliefs with regard to the writing process (the micro-process) and the process of learning to write (the macro-process) in the ESL context. A study consisting of two cases was undertaken to examine the reconstruction of the writer's identity and the evolution of the learner's beliefs in an ESL context. Data for Case A include writings by and interviews with a first-year ESL student; data for Case B include class observations of and interviews with students and their teacher in an ESL writing class. It has been found that the notions of culture, identity, and beliefs are interwoven they work together to reshape learners' beliefs in terms of education and writing and to reconstruct a writer's identity that incorporates multiple influences and multiple intentions. Recommendations are offered for guiding ESL students in the exploration of their first and host cultures and for facilitating the evolution of beliefs and the reconstruction of identities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".