Bibliographic record
Abstract
With this volume of English World-Wide, the online submission process and the subsequent peer-reviewing and online publication ahead of print via Benjamin's Editorial Manager (EM) have been firmly established.By now, both the editorial teams and our authors have acquainted themselves with the intricacies of this tool and increasingly appreciate the many advantages the system provides us with.This is not least due to Heleen Groesbeek's continued support and efforts to improve the system whenever necessary.Between August 2022 and July 2023, well over 60 research papers were submitted via the EM and 15 full papers made it into this volume.The papers published span the entire globe, most of them dealing with varieties of English in specific areas and places, for instance on the African continent (Nigeria, Namibia), or the Americas (Canada, the Falkland Islands, Kansas, Miami), as well as in Asia (Hong Kong, the Philippines, Singapore,), or Australasia (Australia, New Zealand), and Europe (Cornwall), but we also have studies exploring variation across World Englishes.The range of topics dealt with is similarly wide, covering studies in sociophonetics, variational pragmatics, corpus linguistics, grammatical variation, historical sociolinguistics and dealing with questions of grammaticalisation, language contact, lexical levelling, conversational practices, language attitudes, the use of English as a lingua franca and implications for language teaching.This geographic and thematic scope illustrates the breadth of World Englishes research and does justice to the continued efforts to have this adequately represented in our journal.We can only maintain the high standard of our journal and its contributions, because of our reviewers' expertise and support.We are very grateful to the following colleagues, who took the time to provide helpful and constructive feedback (between August 2022
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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 | 0.009 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.189 | 0.168 |
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".