Reading academic English: Carrying learners across the lexical threshold
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
With the growth of English as the lingua franca of work and study, many non-English speakers find themselves needing to attain some level of proficiency in English in order to function in jobs or courses. However, they may have limited time to devote to language learning, and little interest in knowing English outside the work or study context. Responding to these circumstances, English for Specific Purposes (ESP) curriculum designers have attempted to reduce the time frame of learning through domain targeting. They attempt to identify and teach the lexis, syntax, functions and discourse patterns most commonly used in a domain (for chemistry students, test tubes, passive voice, clarification requests and laboratory reports). This approach has given waiters, tour guides and airline pilots enough English to function in their domains after relatively short periods in the classroom. But it runs into complications when the specific purpose is to read extended texts in a professional or academic domain.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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