Debunking “pluri-areality”: On the pluricentric perspective of national varieties
Bibliographic record
Abstract
Abstract Pluricentric approaches to international varieties have been a mainstay in English dialectology since the 1980s, often implied rather than expressed. What is standard lore in many philologies is today questioned in one philology, however. This paper assesses the pros and cons of the so-called “pluri-areal” perspective, which has in the past few years become prominent in German dialectology. Intended to replace the pluricentric model, “pluri-arealist” perspectives affect the modelling of German standard varieties in Austria and Switzerland, among others. Attempting to falsify claims on both sides, this paper argues from an English-German comparative perspective that the idiosyncratic treatment of national varieties in one context is a problem that threatens the unity of the field regarding how the standard is seen in relation to other varieties. It is shown that the base of the “pluri-areal” paradigm is an a-theoretical perspective of geographical variation that adheres implicitly to aOne Standard German Axiom. This meta-theoretical paper suggests three principles to prevent such terminologically-fuelled confusion henceforth.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".