Issues in EAP: A preliminary perspective
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
English for Academic Purposes (EAP) – the teaching of English with the specific aim of helping learners to study, conduct research or teach in that language – is an international activity of tremendous scope. It is carried out in four main geographical domains, each of which exhibits particular characteristics and purposes. It is carried out, first, in the major English-speaking countries (the US, UK, Australia, Canada and New Zealand), where large numbers of overseas students whose first language is not English come to study. It is conducted, second, in the former colonial territories of Britain (and less importantly the United States) where English is a second language and is used as the medium of instruction at university level. It is conducted, third, in countries which have no historic links with English, but which need to access the research literature in that language (the countries of Western Europe, Japan, China, Latin America, Francophone Africa and others).1 And finally, EAP is now increasingly being offered in the countries of the former Soviet-bloc, as they seek to distance themselves from the influence of Russia and its language and position themselves as participants in the increasingly global economy and academic community.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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