Bibliographic record
Abstract
This paper illustrates how contact can facilitate the development of phonemic and allophonic splits by presenting results from a study of vowel variation and change in Toronto Cantonese, a variety of Cantonese spoken in a heritage language contact setting. The data includes hour-long sociolinguistic interviews from speakers from two different generational backgrounds. The vowel space of each of 20 speakers was created based on F1 and F2 measurements of 105 tokens per speaker (15 tokens for each of 7 monophthongs). This paper focuses on the results for two of the mid vowels (/ɛ/ and /ɔ/) where there is evidence for the development of two phonetically conditioned splits based on velar context. A third split, discussed in Tse (In Press), may have triggered the development of these two splits among second-generation speakers. Phonological influence from Toronto English is one possible explanation for these splits. Overall, the results of this study may partially address why there are more documented cases of vowel mergers than vowel splits. Splits may be more likely to develop in certain contact settings that have been under-researched in the variationist sociolinguistics literature.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".