<scp>take up #9</scp>as a semantic isogloss on the Canada‐US 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
ABSTRACT This paper explores semantic isoglosses of polysemous words, an understudied aspect of the Canada‐US border by drawing on take up #9 , an isogloss that appears to be spreading through the mainland Canadian population. The variable, which is approached from a philological‐lexicographic as well as a quantitative‐statistical perspective, is interpreted in the light of recent European cross‐borders studies. Analogues with the situations in Austrian German (Austria‐Germany) and British English (Scotland‐England) are drawn. Set in a pluricentric framework, this paper argues that the Canada‐US border remains a productive linguistic divide. Moreover, it is suggested that types of unexplored lexico‐semantic variables may be responsible for some identity work across this international border, one of only two contiguous borders among the Englishes of the Inner Circle.
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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 | 0.007 |
| 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) | 0.002 | 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 it