Bibliographic record
Abstract
Another busy (editorial) year has come and gone.We are reporting for the period between August 2023 and July 2024, when we received 70 manuscripts for review from authors around the globe and all the Kachruvian circles: from EFL countries in Europe and China to ESL contexts in Asia and Africa and ENL countries in the southern hemisphere.Of these, the usual 13 full papers made it into the current volume.The Englishes discussed in the published papers include regional varieties in the UK and the Philippines, variation across the Kachruvian circles (the model continues to serve as a reference frame), as well as Englishes in North America, South Asia and South Africa.Topic-wise, research in this volume looks at urban and rural accents in the UK as well as ethnic accents in Toronto, aspects of lexical and grammatical variation in Britain and South Africa but also sociolinguistic topics like codeswitching and variationist pragmatics.The first issue adds a novel spice to the familiar mix in that it includes a contribution that discusses World Englishes from the perspective of journal editors and the role they play in norm orientation.The diversity of methodologies adopted in the papers (qualitative, quantitative and mixed) aptly reflects the range of topics that researchers in the field are working on and the corresponding range of analytical tools that are needed to capture the rich tapestry made up from varieties of English around the world.A major part of the work that goes into the production of a journal comes from the generous support of many colleagues around the world who give of their (typically limited) time freely to take on reviews.It is their expertise and constructive criticism that help maintain the high standard of the published contributions.For the reporting period (August 2023 and July 2024) we gratefully acknowledge the support that was provided by reviewers on manuscripts (including those that had to be rejected), including
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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 | 0.012 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.096 | 0.085 |
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".