Language Variation - European Perspectives III
Bibliographic record
Abstract
Language Variation – European Perspectives III contains 18 selected papers from the International Conference on Language Variation in Europe which took place in Copenhagen 2009. The volume includes plenaries by Penelope Eckert (‘Where does the social stop?’) and Brit Mæhlum (on how cities have been viewed by dialectologists, sociolinguists – and lay people). In between these two longer papers, the editors have selected 16 others ranging over a wide field of interest from phonetics (i.a. Stuart-Smith, Timmins and Alam) via syntax (Wiese) to information structure (Moore and Snell) and from cognitive semantics (Levshina, Geeraerts and Spelman) to the perceptual study of intonation (Feizollahi and Soukup). Several of the papers concern methodological questions within corpus based studies of variation (Buchstaller and Corrigan, Vangsnes and Johannessen, and Ruus and Duncker). Taken as a whole the papers demonstrate how wide the field of variation studies has become during the last two decades. It is now central to almost all linguistic subfields.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".