The Development of <i>And Stuff</i> in Canadian English: A Longitudinal Study of Apparent Grammaticalization
Bibliographic record
Abstract
This paper examines the development of and stuff, a general extender (GE), in Canadian English in longitudinal perspective. Previous research (Cheshire 2007; Tagliamonte & Denis 2010; Pichler & Levey 2011) finds suggestive evidence that and stuff and other GEs have undergone grammaticalization over their development. However, when viewed in apparent time, there is little evidence of ongoing grammaticalization; rather only vestiges of apparent previous grammaticalization remain. This paper takes up Pichler and Levey’s (2011) call for an appropriate real-time benchmark of comparison to enable a more thorough understanding of the historical development of these features. A collection of oral histories recorded in the 1970s and 1980s with elderly residents of three communities in southern Ontario, Canada, is used as a proxy for comparison to Tagliamonte and Denis’s (2010) analysis of the Toronto English Archive. By tracking the development of and stuff over more than a century of apparent time, this paper finds three changes in progress: (1) a lexical replacement such that and stuff becomes the majority variant in the variable system; (2) a morphological clipping process such that longer GEs such as and stuff like that lose the comparative element like that; and (3) the semantic bleaching of the set-marking meaning of and stuff. While this last change is a necessary part of grammaticalization, in the absence of phonetic reduction, decategorialization, and pragmatic shift, it is not sufficient evidence according to grammaticalization theory (e.g., Heine 2003; Traugott 2003; Diewald 2010).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".