A systemic functional linguistic approach to usage-based research and instruction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The present chapter illustrates how Systemic Functional Linguistics (SFL) can inform a usage-inspired approach to researching and teaching L2 writing in a postsecondary context. We first outline an SFL perspective to multilingual academic literacy development and then illustrate this perspective by means of longitudinal, corpus data on nominalization use in the English academic writing of francophone university students over four years. By means of quantitative indicators (nominalization frequencies, erroneous forms, measures of L2 proficiency scores and syntactic complexity) and qualitative analyses (of the discourse functions that nominalization serve), we argue that French-speaking writers’ use of nominalization in English indexes both language-specific and language-interdependent aspects of multilingual academic literacy development. We conclude with implications for further SFL-informed research and instruction that aims to promote multilingual academic literacy development by raising crosslinguistic awareness of the forms and functions of nominalization in academic discourse.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it