Book Reviews
Bibliographic record
Abstract
Carmen Fought (ed.), 2004, Sociolinguistic Variation: Critical Reflections. Oxford Studies in Sociolinguistics. New York: Oxford University Press, xv + 214 pages, ISBN 0‐19‐517039‐3 (hbk) Diana Yankova, 2004, Legal Language Made Simple: Statutory Provisions in English and Bulgarian. Sofia: Tip‐Top Press, 189 pages, ISBN: 954‐8964‐60‐0 Gunilla Anderman and Margaret Rogers (eds.), 2005, In and Out of English: For Better, For Worse? Clevedon/Buffalo/Toronto: Multilingual Matters, 303 pages, ISBN 1‐85359‐788‐0 (hbk), ISBN 1‐85359‐787‐2 (pbk) Ulrich Ammon et al., 2004, Variantenwörterbuch des Deutschen. Die Standardsprache in Österreich, der Schweiz und Deutschland sowie in Liechtenstein, Luxemburg, Ostbelgien und Südtirol. Berlin/New York: Walter de Gruyter, LXXV + 954 pages, ISBN 3‐11‐016574‐0 Werner Hüllen, 2005, Kleine Geschichte des Fremdsprachenlernens. Berlin: Erich Schmidt Verlag, 184 pages, ISBN 3‐503‐07946‐7 Helena Halmari and Tuija Virtanen (eds.), 2005, Persuasion Across Genres: A linguistic approach. Amsterdam/New York: John Benjamins, viii + 257 pages, ISBN: 90‐272‐5373‐0 (EUR), 1‐5811‐588‐7 (US) Michael Ashby and John Maidment, 2005, Introducing Phonetic Science. Cambridge Introductions to Language and Linguistics. Cambridge University Press, viii + 222 pages, ISBN: 0‐521‐00496‐9 Ewa Da̧browska, 2004, Language, Mind and Brain. Edinburgh University Press, 280 pages, ISBN 0‐7486‐1475‐3 (pbk), 0‐7486‐1475‐5 (hbk) Response to Kumiko Murata's review of Genetically Modified Language
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.476 | 0.421 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".