A Variationist Analysis of Quotatives in Ottawa English
Bibliographic record
Abstract
This study investigates variation and change in the quotative system in Ottawa English and provides a comparative sociolinguistic analysis of its development. A corpus of spontaneous speech of 30 speakers of Ottawa English stratified according to age and sex is compiled to provide a quantitative analysis of the effects of some social and linguistic factors on the distribution of quotative variants in this variety. The results show that the choice of quotative variants is socially and linguistically constrained. The results also show that the distribution of the quotative variants in Ottawa English has changed due to the incorporation of the incoming variant be like. The results also confirm that younger speakers use this variant more than their older counterparts with younger female speakers leading the change. Moreover, the results provide a further piece of evidence in favor of the advanced stage of grammaticalization that be like has undergone. Furthermore, the results demonstrate that while be like is completely absent from the speech of older speakers in Ottawa English, it seems that this variant has eventually found its way to the discourse of older female speakers in Ottawa English. This result in particular shows the efficacy of conducting more variationist studies on an intensively discussed variable to provide updates regarding the level of variation and change it has reached. Keywords: Canadian English, Language Variation & Change, Ottawa English, Quotative System, Variationist Approach.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".