The Stuff of Change: General Extenders in Toronto, Canada
Bibliographic record
Abstract
This article examines general extenders (GEs) in the English spoken in Toronto, Canada, using a 1.2-million-word corpus stratified by age, sex, and education. Employing quantitative techniques, the authors assess the nature of the system, particularly the possibility that it has undergone recent grammaticalization. Diagnostic tests for phonetic reduction, decategorization, semantic change, and pragmatic shift reveal that only decategorization is visible in apparent time. Otherwise, older and younger speakers share most of the same patterns. Yet there is a dramatic shift happening in that the form stuff is rapidly becoming the predominant GE.The authors conclude that in contrast to the United Kingdom, the GEs in Toronto are not grammaticalizing but are undergoing lexical replacement. These findings suggest that discourse-pragmatic features may differ markedly across varieties and further that putative indicators of grammaticalization may not always operate in tandem. GEs provide a unique opportunity to study social and linguistic influences on discourse-pragmatic variation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".