Geolinguistic diffusion and the U.S.–Canada border
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
The way in which language changes diffuse over space—geolinguistic diffusion—is a central problem of both historical linguistics and dialectology. Trudgill (1974) proposed that distance, population, and linguistic similarity are crucial factors in determining diffusion patterns. His hierarchical gravity model has made correct predictions about diffusion from London to East Anglia, but has never been tested across a national boundary. The aim of this article is to do so using data from both sides of the U.S.–Canada border. Two cases are examined: the non-diffusion of phonetic features from Detroit to Windsor and the gradual infiltration into Canadian English of American foreign (a) pronunciations. In both cases, the model makes incorrect predictions. In the first case, it is suggested that the model needs a term representing a border effect, and that the diffusion of phonetic features is constrained by structural, phonological factors; in the second, a traditional wave theory of diffusion appears to fit the data more closely than a hierarchical model.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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 it