Bibliographic record
Abstract
Abstract Prevelar /æ/-raising (bag-raising) is a process in which some speakers of North American English raise /æ/ before /ɡ/ but not /k/. Self-report data suggests that this process occurs in Canada and regions of the United States close to the Canadian border. Acoustic data seems to support this finding, with evidence for bag-raising across Canada and in the Pacific Northwest, the Upper Midwest, and California in the United States. However, this evidence is somewhat limited, particularly as there is no documentation of bag-raising (or lack thereof) in regions where it is not expected to occur. The current study adds to our knowledge about the distribution of the production of bag-raising by acoustically documenting its production in Colorado, where it is not expected to occur and has not been previously studied, and Ontario, where it is expected to occur and has been studied but not specifically targeted. The results indicate that Ontarians bag-raise while Coloradans do so little, if at all. Furthermore, there is a fair amount of variation in bag-raising across participants that cannot be accounted for by region alone.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".