Bibliographic record
Abstract
This study examines production of the vowels /æ/, /ɛ/, and /e/ among three different English-speaking ethnic populations in Manitoba, Canada, focusing on patterns of raising and vowel overlap in prevelar contexts. Although raising of /æ/ before /ɡ/ has been documented for the Prairies region of Canada generally, its specific occurrence in Manitoba as well as the occurrence of vowel merger(s) there has not previously been examined in detail. This study finds that pre-velar patterns are distinguished by coda voicing, with voiceless /k/ producing lowering and some retraction while voiced /ɡ/ and /ŋ/ produce similar raising and especially fronting patterns in preceding /æ/ and /ɛ/. Statistical analysis of spatial and temporal qualities shows that, while complete merger is not observed between any of the three vowels, there is much more substantial overlap in their productions before the voiced velars than in other contexts; in contrast, the voiceless velar /k/ is associated with productions which often substantially diverge from these. The results suggest that Manitoba speakers' productions of these vowels share some features of other dialects with velar-affected productions, but the arrangement of these features in Manitoba may represent a unique configuration having a potential, incipient, or early-stage prevelar merger of /æ/ and /ɛ/, mainly without the participation of /e/. Social factors such as conservatism and extra-local affiliation are also found to play a role in production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".