Contrastivity and comparability: pragmatic variation across pluricentric varieties
Bibliographic record
Abstract
Abstract The recent pragmatic turn in the study of pluricentric varieties marks a shift in analytical focus, with increasingly more research contrasting the conventions of language use and interaction across pluricentric varieties. This turn demands new data types and new methods of analysis which uphold the principles of contrastivity and comparability. Addressing this basic requirement for the case of cross-varietal speech act analyses, the present article examines the contextual factors to be considered in the choice of data types and the potential definition and usability of a pragmatic variable in speech act analyses across data types. These considerations are applied to a cross-varietal analysis of responses to thanks in direction-giving exchanges across English in Canada, England and Ireland. The study highlights the frequent necessity of a multi-faceted definition of the pragmatic variable. In addition, challenges of contextual equivalence which emerge in the course of the analysis highlight a basic need for research to regularly re-examine the linguistic context and the definition of the pragmatic variable and to potentially redefine the variable during the analytical process. The contrastive analysis reveals a more extensive use of routinised responses to thanks in the Canadian English data relative to the Irish English and English English data. A more complex closing, with more continuations and confirmation checks, is shown to characterise the Irish English data, a finding which is suggested to potentially relate to a strong orientation towards hospitality in the Irish context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".