Comparative Sociolinguistic Insights in the Evolution of Negation
Bibliographic record
Abstract
There are three ways of expressing negation on indefinites in English: any-negation (I didn’t have any money), no-negation (I had no money) and negative concord (I didn’t have no money). These variants have been competing diachronically in a change in progress, where the newest variant any-negation is increasing at the expense of the oldest variant no-negation (Tottie 1991a, 1999b, Varela Pérez 2014). This raises the questions: What is the current state of this variability? Is the variation socially evaluated? What does this reveal about linguistic change? Our comparative quantitative sociolinguistic analysis of vernacular speech corpora from Northern England and Ontario, Canada reveals that no-negation is stoutly retained in Britain but is less frequent in Canada. Linguistic constraints on the variation hold cross-dialectally: functional verbs retain no-negation, while lexical verbs favour any. However, the social embedding of the variation is community-specific. Where the change to any-negation is more advanced, i.e., Canada, there are no significant social effects: the variation between any-negation and no-negation appears stable. In England, where no-negation is conserved to a greater extent, there are effects of speaker sex and education, with men and less-educated speakers favouring no-negation. Furthermore, both of the UK communities (North East England and York) display age-grading trends which suggest that the prestige associated with any-negation historically has persisted over time. While the communities share a common variable grammar, the social value in choosing a variant is localised and reflects the status of the change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".