BOOK REVIEW: English Studies Beyond the ‘Center’: Teaching Literature and the Future of Global English
Bibliographic record
Abstract
In the world of globalized English, the focus is more on learning practical skills of language than on language as a tool for expression. This concentration has marginalized English literary studies. The very little scholarship on teaching English literature either does not come from within the discipline or is not generally targeted at an EFL context. English Studies Beyond the ‘Center’ offers a long-awaited take on the why and how of teaching English literature in an EFL context from the perspective of a literature specialist. The volume is an attempt to address three interdependent issues: the place of English literature education in the world of globalized English studies, the main goal behind teaching literature as part of English studies and the way literature is taught. Indeed it seeks to “make a case for literary study in this expanded, essential, globalized English studies” (p. 1). As a Canadian educated in North America and a professor teaching in Japanese universities, Myles Chilton brings in his educational backgrounds from the ‘center’ of English studies and his experiences of teaching literature from universities ‘beyond the center’ to this book, making it very useful for people who are involved in teaching English literature especially in an EFL context.
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.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".