Investigating Cohesion and Coherence Discourse Strategies of Chinese Students with Varied Lengths of Residence in Canada
Bibliographic record
Abstract
This study examines how three age-on-arrival (AOA) groups of Chinese-background ESL students use two types of cohesive devices on a standardized essay exam. A discourse analysis of 90 first-year students’ expository writing samples was conducted to ascertain how factors such as first language (L1) and length of residence (LOR) in Canada influence a student’s ability to create cohesive and coherent writing. The study uses both quantitative and qualitative methods to explore how Canadian-born Chinese (CBC) students use lexical and referential discourse markers. Twelve essay features of this group of Generation 1.5 students are compared with those of two other cohorts of Chinese students with a shorter LOR. Key writing variables that measure academic writing proficiency were quantitatively analyzed to compare the expository writings of the CBC cohort with those of the later AOAs. Results indicate that synonymy and content words distinguish the writings of the CBC students from those of their later-arriving peers. A qualitative analysis of one CBC essay reveals that a more flexible and contextualized approach to evaluating writing by longterm Generation 1.5 students is required to acknowledge fully the productive lexical and discoursal strengths of these students.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".