Learning English Rhetoric and Composition as A Vietnamese Student
Bibliographic record
Abstract
This study centers around Vietnamese students, with a comparison with East and Southeast Asian students who share the same cultural idea, at higher education level who want to acquire better writing skills in English in and out of academic settings. Since English is not the students' first language, they normally craft an essay from the vocabulary that they know. This is understandable, but a good piece of writing in standard American English is not supposed to be traced word by word. Understanding this fact in-depth and practicing it regularly is the core requirement for English major students. In return, they can join any workplace with their strong writing skills that they have to acquire during their undergraduate years, or more if they attend graduate schools. This group of students is known to be timid since they were raised in a collectivistic community in which many of them make their higher education choices based on firstly the current trend, then what is suitable for them. Thus, by making a bolder choice of declaring English as a major, double major, or minor, they could have better insight into English rhetoric and composition to apply them as a multi-meaning sign to their writings properly.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".