Bibliographic record
Abstract
Cohesion is a very important part of learning English. The Cohesion Theory of Halliday and Hasan is of great importance for people to acquire the knowledge of cohesion. This study is aimed at applying this Cohesion Theory in CET-4 listening comprehension which is an important test for Chinese college students. This study uses the test papers of CET-4 in June 2021 as examples to demonstrate that it is obvious that there are certain cohesive relations between the listening materials and the correct answers. It is also practicable to apply the Cohesion Theory in listening comprehension of CET-4. It mainly analyzes the cohesive devices applied in figuring out the correct choices by understanding the cohesive relations between the listening materials with the right answers. It demonstrated obviously that there exists the cohesive relations between the listening materials with the right answers in the test, and both the grammatical device and lexical device are often used interactively. The cohesive devices can serve as the important clues for students to make the right choices. The findings of this study suggest that the application of the Cohesion Theory in CET-4 listening comprehension is practicable and effective. It can not only help the students get good performance in the CET-4 tests, the same approach can also be used in other important tests.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".