The ain't constraint: Not-contraction in early African American English
Bibliographic record
Abstract
Studies of negation in African American English (AAE) typically focus on its most salient exponents, ain't and negative concord. Because ain't arose during the development of auxiliary- and not-contraction in Early Modern English, an interesting question is whether constraints on ain't can be attributed to more general constraints on contraction. This article examines the constraints on not-contraction in three varieties argued to be representative of Early AAE. Although the analysis is complicated by the ever-narrowing variable context of ain't and by the competition of not-contraction with auxiliary contraction, results are largely parallel across the three varieties, pointing to a common origin. The parallels between ain't and not-contraction provide evidence that ain't is the extension of more general processes of contraction. The most consistent effect, the presence of negative concord, is argued to reflect a recurrent process of reinforcement in the history of English negation.The data on which this study is based were extracted from corpora housed in the Sociolinguistics Laboratory at the University of Ottawa. I gratefully acknowledge Professor Shana Poplack's permission to use these data. Earlier versions of this article were presented at the annual meeting of the American Dialect Society (Washington, DC, January 2001) and the third U.K. Language Variation and Change conference (York, U.K., July 2001). The analysis benefited from discussions with and comments from Greg Guy, Dennis Preston, Jennifer Smith, and Gerard Van Herk, as well as several anonymous reviewers. Special thanks go to Sali Tagliamonte and Malcah Yaeger-Dror, whose comments substantially improved the article, and to Anthony Warner for help with translating the Old English examples. Any remaining errors are my own responsibility.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".