The pre-nasal allophonic splitting of /ɛ/ in Toronto Heritage Cantonese
Bibliographic record
Abstract
Muysken (2019) has argued that the most convincing cases of contact-induced change in heritage languages involve the dominant language having two distinctions mapping on to one (2-to-1). Evidence of such a case from Toronto heritage Cantonese will be discussed. Toronto English (the dominant language) has an allophonic split in which the TRAP vowel is raised and fronted in pre-nasal contexts. This is argued to influence the development of a similar allophonic split, led by lower proficiency speakers, in which Cantonese /ɛ/ is fronted before nasal consonants. The lack of an /ɛ/ split in Hong Kong Cantonese provides further support for contact-induced change. Unlike cases of a 1-to-2 mapping leading to a loss of a distinction in the heritage language (which can be argued to be internally motivated), this contact-induced split leads to increased phonological complexity, which is inconsistent with a deficit view of heritage language speech 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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".