Bibliographic record
Abstract
The History of Late Modern Englishes provides an accessible and student-friendly introduction to the history of the English language from the beginning of the eighteenth century up until the present day. Taking an activity-based approach, this text ensures that students learn by engaging with the fascinating evolution of this language rather than by simply reading about it. The History of Late Modern Englishes: • Covers the development of Englishes around the world, not only in the British Isles, but also in the United States, Canada, India, Singapore, Australia, New Zealand, and Melanesia, as well as in other countries around the world where English is used as a lingua franca; • Accommodates the needs of both native and non-native speakers of English, with helpful features such as a glossary of key terms and questions to guide the reader through the book; • Includes activity sections and discussion points to help students engage with the text; • Is accompanied by e-resources which include further activities and additional coverage of points of interest in the book. Written by an experienced teacher and author, this book is an essential course textbook for any module on the history of English and the perfect accompaniment to the author’s own The History of Early English.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".