Deconstructing variation in pragmatic function: A transdisciplinary case study
Bibliographic record
Abstract
Abstract Despite recent advances (e.g. Cheshire 2007; Pichler 2010; Denis 2015), discourse-pragmatic variables continue to challenge variationist theory and methods. An overarching dilemma concerns multifunctionality, raising difficulties for semantic equivalency and the circumscription of the variable context. In this article we present a case study to illustrate that deconstructing a discourse-pragmatic marker into its composite parts reveals clear criteria for disambiguating its principal function and its contextually derived functions. The discussion centres on the pragmatic markerehin Canadian English. We illustrate that its multifunctionality is derivable from four parts: principal function, syntactic context, prosodic context, and discourse context. Our deconstruction uses a two-pronged methodology, drawing on storyboard elicitation and sociolinguistic interview data, which mutually reinforce our theoretical arguments. Under this transdisciplinary lens, the exponents of form and function become predictable, constrainable, and systematically derivable for probabilistic modelling within and across speech communities. (Confirmationals, multifunctionality, pragmatic markers,eh,speech acts)*
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| 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".