Crossroads at the linguistic market: Canadian raising and post-vocalic-R on Mount Desert Island
Bibliographic record
Abstract
Local identity practices are not as straight-forward as originally predicted (Labov 1972a, 1963). In this thesis, I build on previous work on local identity practices (e.g. Blake and Josey 2003), Josey (2004), Wolfram (1997) in an investigation of local feature maintenance and local identity practice on Mount Desert Island, a tourist-dependent community in Eastern New England. Based on analysis of interviews with 12 native speakers, I find that a local feature, the dropping of post-vocalic-R is moribund in the community. The r-less variant is maintained among older speakers. A gender and age pattern with a capital pattern (Bourdieu 1972, 1986, 1991) was found. I also examine the community’s use of Canadian Raising (Chambers 1973). I find that /aj/ and /aw/raising are introduced to the community with a great range of social variation as found in other communities in the northern US where raising is observed (e.g. Vance 1987, Dailey-O’Cain 1997).
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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 | 0.002 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".