A Corpus-Based Study of Contrastive/Concessive Linking Adverbials in Spoken English of Chinese EFL Learners
Bibliographic record
Abstract
This paper reports a corpus-based study on the usage patterns of contrastive/concessive linking adverbials in Chinese EFL learners’ speech. The results suggest that: a) compared with English native speakers, the Chinese learners tend to significantly underuse contrastive/concessive adverbials in their speech; b) while both the learners and the native speakers rely heavily on a limited set of contrastive/concessive adverbials in their speech, the learners are found to overuse certain adverbials and underuse others; c) the learners prefer to use contrastive/concessive linking adverbials in initial position of a sentence. The factors underlying what is found in learners’ use of contrastive/concessive adverbials are multifold, such as mother tongue influence, teaching instructions, and semantic misuse. Pedagogical implications of the present study are drawn and research suggestions are presented at the end of the paper.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".