Not always variable: Probing the vernacular grammar
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Written and spoken language are known to differ substantially (Biber, 1988; 1995; Biber, Johansson, Leech, Conrad, & Finegan, 1999). Standard written language is highly uniform and governed by prescription, whereas the vernacular is most revealing of structured heterogeneity (Weinreich, Labov, & Herzog, 1968). We focus on four English morphosyntactic variables that problematize assumptions about the nature of variation in the vernacular: the genitive, the comparative, the dative, and relative pronouns. Each is characterized in casual speech by functional divides that reflect discrete configurations of variant use. After detailing the patterning of these variables in speech, we explore a characteristic arguably shared by each: its historical pathway into the language, where analogy and prestige were powerful motivations for variant choice. We suggest that this combination of systemic and social factors contributed to the nature of these variables in the vernacular grammar. Furthermore, we advocate for greater scrutiny of written and spoken data and the outcomes of change from above and below within each register. The type of innovation and its trajectory may affect the nature of the emergent variable grammar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it