Local Spoken Here: The Phonology of Oregon English
Bibliographic record
Abstract
Labov’s division of the U.S. into three dialect areas defines the West (the third and largest of these) in relation to other North American dialects. The absence of “Canadian ” Raising in /aw/ distinguishes it from Canadian English, the low back merger from the North East, absence of /ow / fronting from the Midlands, and absence of glide deletion in /ay / from the South (Labov et al. 2002). While there have been many studies of Californian English, other areas such as the Pacific Northwest have seen relatively little linguistic inquiry, despite the fact that the work which has been done suggests that the situation is more complex than is generally thought. Some findings in the area include prominent use of creaky voice (Ingle et al. 2005, Ward 2003), /_/ raising towards /e / when followed by /g / (Conn 2002), and lexical differences (Ward 2003), and some scholars have suggested that the Pacific Northwest constitutes the most distinct dialect in the West (Ward 2003). This paper is an investigation into the English spoken by Oregonians, using interviews with four consultants (age/class matched) from Corvallis, a small town in the Willamette Valley south of Portland. The formant values of 180 tokens (three tokens of 9 simple vowels from each speaker) were measured using Praat, the results of which support those found by others who have done work in the area (Conn 2002, Ingle et al. 2005, Ward 2003) and
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.006 | 0.001 |
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".