The production and perception of prevelar/æ/-raising by Canadian and American english speakers
Bibliographic record
Abstract
Pre-velar /æ/-raising occurs when /æ/ is raised before /g/ relative to other contexts. This study examines the extent of phonological conditioning of /æ/-raising between /g/ and /k/ in production and perception. First, I tested the extent to which 18 Canadian and American English speakers raise /æ/ before /g/ (vs. /k d t/) using a wordlist reading task with words containing /æ/ and /ɛ/ in the relevant contexts. Consistent with previous studies (Stanley, 2018; 2019), Canadians, but not Americans, tended to raise /æ/ before /g/. Second, I tested whether the same effect exists in perception using a forced-choice nonce-word identification task with 9-step continua from /æ/ to /ɛ/ before /g/ and /k/. Are speakers who /æ/-raise in production more likely to identify the manipulated vowel as /æ/ before /g/ than /k/, especially when it is ambiguous? Perception has not been tested in previous work, though anecdotal evidence suggests differences in perceptual saliency – Americans, but not Canadians, are aware of /æ/-raising, suggesting that a relationship may exist. Contrary to the anecdotal evidence, there was no correlation between production and perception at the group (nationality) or individual level. However, /æ/ was perceived more before /g/ than /k/ overall, suggesting that /æ/-raising influences perception.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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 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".