Phonetic and Lexical Encoding of Tone in Cantonese Heritage Speakers
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Bibliographic record
Abstract
Heritage speakers contend with at least two languages: the less dominant first language (L1), that is, the heritage language, and the more dominant second language (L2). In some cases, their L1 and L2 bear striking phonological differences. In the current study, we investigate Toronto-born Cantonese heritage speakers and their maintenance of Cantonese lexical tone, a linguistic feature that is absent from English, the more dominant L2. Across two experiments, Cantonese heritage speakers were tested on their phonetic/phonological and lexical encoding of tone in Cantonese. Experiment 1 was an AX discrimination task with varying inter-stimulus intervals (ISIs), which revealed that heritage speakers discriminated tone pairs with disparate pitch contours better than those with shared pitch contours. Experiment 2 was a medium-term repetition priming experiment, designed to extend the findings of Experiment 1 by examining tone representations at the lexical level. We observed a positive correlation between English dominance and priming in tone minimal pairs that shared contours. Thus, while increased English dominance does not affect heritage speakers' phonological-level representations, tasks that require lexical access suggest that heritage Cantonese speakers may not robustly and fully distinctively encode Cantonese tone in lexical memory.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it