Foreign (a) in North American English: Variation and Change in Loan Phonology
Bibliographic record
Abstract
Previous research has shown that Canadian English displays a unique pattern of nativizing the stressed vowel of foreign words spelled with the letter , like lava, pasta, and spa, known as foreign (a), with more use of /æ/ (the trap vowel) and less use of /ah/ (the palm vowel) than American English. This paper analyzes one hundred examples of foreign (a), produced by sixty-one Canadian and thirty-one American English-speakers, in order to shed more light on this pattern and its current development. Acoustic analysis is used to determine whether each participant assigns each vowel to English /æ/, /ah/, or an intermediate category between /æ/ and /ah/. It reports that the Canadian pattern, though still distinct, is converging with the American pattern, in that Canadians now use slightly more /ah/ than /æ/; that men appear to lead this change but this is because they participate less than women do in the Short Front (Canadian) Vowel Shift; that intermediate vowel assignments are comparatively rare, suggesting that a new low-central vowel phoneme is not emerging; that the Canadian tendency toward American pronunciation is not well aligned with overt attitudes toward the United States and American English; and that the national differences in foreign (a) assignment result not from structural, phonological differences between the dialects so much as from a complex set of sociocultural factors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".