Pre-velar /æ/-raising in Ontario and Colorado English: Production, Perception and Metalinguistic Awareness
Bibliographic record
Abstract
Pre-velar /æ/-raising (BAG-raising) is a process in which some speakers of North Amer- ican English raise /æ/ before /g/, but not /k/. This process occurs in parts of Canada (e.g. Boberg, 2008), and in the Pacific Northwest (e.g. Freeman, 2021) and Upper Midwest (e.g. Koffi, 2013) in the US. While documentation of the production of BAG-raising is limited, less is known about its perception. Previous studies find no difference between how BAG-raisers and non-raisers perceive raising (Freeman, 2019; Sullivan, 2020a); however, anecdotal evidence suggests individuals from dialect regions without BAG-raising perceive the raised /æ/ in [æg] words as distinct from its unraised counterpart while those from BAG-raising regions do not. This dissertation seeks to establish if listeners hear raised and unraised /æ/ as distinct pronunciations, and if this is conditioned by production, metalinguistic awareness and/or phonological context. First, a metalinguistic awareness survey confirmed anecdotal evidence for differences in metalinguistic awareness between individuals from BAG-raising and non-raising regions. Individuals from non-raising regions had more metalinguistic awareness than those from BAG-raising regions. The study demonstrates that it may be possible to quantify metalinguistic awareness, though more work is needed to establish how best to do so, and which aspects of folk linguistic awareness (Preston, 1996) different tasks are tapping into. Next, a production study extended knowledge about the distribution of the production of BAG-raising to Colorado, where it has not been previously studied, and Ontario, where it has been studied, but not specifically targeted (Boberg, 2008; Sullivan, 2020a). This study showed that BAG-raising occurs in Ontario, but not Colorado. Finally, an AX discrimination task explored if speakers could discriminate raised and unraised /æ/ and if this was conditioned by their individual degree of BAG-raising, their metalinguistic awareness or the phonological context of /æ/. Listeners with higher degrees of BAG-raising discriminated raised and unraised /æ/ less than those with lower degrees of BAG-raising, but only before /g/, suggesting that production is implicated in perception and that mental representations are formed based on an individual’s production and the phonological context in which a sound occurs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".