The role of communicative purpose in describing and interpreting lexico-grammatical variation in L2 writing
Bibliographic record
Abstract
The exploration of how communicative purpose influences second language (L2) writing has a long-standing history. This study adapted the Register Functional (RF) approach as proposed by Biber et al. (2021) to investigate linguistic patterns in essays written in English for two different communicative purposes (narrative and descriptive) by the same L2 writers in an EFL context. We analyzed 55 narrative and 55 descriptive essays ( N = 110) written by the same 55 students during one exam period. Using selective features and lexical analyses to identify key grammatical features and their lexical realizations. The study identified distinguishing linguistic features between narrative and descriptive essays that can be functionally interpreted and related to the communicative purpose of each essay type. Based on the findings, we illustrate how different communicative purposes have the potential to enhance L2 writers’ use of diverse lexico-grammatical features when writing.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".