An Empirical Study on Information Prominence Reflected in Sentence Structures of Chinese College EFL Argumentative Writing
Bibliographic record
Abstract
<p>Prominence, as an important dimension of cognitive construal, refers to the capacity to evoke a certain substructure as the focus of attention, which can be materialized in a variety of semantic and grammatical expressions (langacker, 1987). Subject of a sentence (Zhang, 2011) and specific sentence structures (Lin, 2013) can bring a substructure into salience by highlighting it in a specifically grammatical place. Accordingly, the place of subject or the specific sentence structures which are applied to emphasize certain information can reflect a writer’s intention of prominence. Thus, this essay will take prominence of Langacker’s cognitive construal as theoretical basis and has an empirical study on information prominence of 20 argumentative writing papers written by Chinese college EFL learners from Leshan Normal University. By categorizing the sentences of each sample into five types of structures－link verb sentence, active sentence, passive sentence, non-finite verbs as subject and the specific sentence patterns, and referring to the statistics of sentence structure application and the specific writing contents, it is found out that the writers are inclined to highlight subjective or static information, which leads to subjectivity and powerlessness of argumentation.</p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".