The Canadian Shift: Its Acoustic Trajectory and Consequences for Vowel Categorization
Bibliographic record
Abstract
The Canadian Vowel Shift (CS), generally described as a systematic lowering and backing of the front lax vowels (/ɪ, ɛ, æ/; as in KIT, DRESS, and TRAP), has been investigated by several researchers over the last two decades (see Boberg 2005, 2008, 2010; Clarke, Elms & Youssef 1995; Hoffman 2010; Labov, Ash & Boberg 2006; Roeder & Jarmasz 2010; Sadlier- Brown & Tamminga 2008, among others). Using apparent-time comparisons of older and younger Canadians’ vowel spaces, these studies do not always agree on the acoustic trajectory of the CS, notably whether the front lax vowels are principally receding and/or lowering; perhaps these disagreements are unsurprising given the ongoing nature of the vowel shift, the variety of birth years interviewed, and the studies’ methodological differences and diverse locales. Boberg (2005) found /ɛ/ to be retracting and /æ/ to be lowering and then retracting in the speech of Anglophone Montrealers; this paper addresses the current apparent-time trajectory of the CS in one Montreal community. In addition, though several studies have investigated the CS in vowel production, nearly none (save De Decker 2010) have probed its effect on the perceptual categorization of vowels. This paper also introduces a perception experiment carried out with the same participants interviewed for production data.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".