Bibliographic record
Abstract
Abstract This study examines path encoding in motion event expression in Cantonese spoken in Toronto and Hong Kong using a comparative variationist methodology informed by motion event typology. It investigates the linguistic and social factors relevant to variation in directional self-motion event expression in Cantonese as spoken by two generations of speakers in Toronto and homeland speakers in Hong Kong. All relevant examples of self-motion event descriptions found in the spontaneous speech of 23 speakers in sociolinguistic interviews from the Heritage Language Documentation Corpus are compared intergenerationally and diatopically. The results suggest stable variation in Hong Kong but change in Toronto. Changes in Toronto are best explained as language-internal change following universal principles rather than simplification or contact with English. This study contributes to literature on the effect of language contact on motion event expression in multilinguals, while also highlighting the importance of considering first-generation immigrants as the baseline for second-generation speakers in addition to homeland speakers.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".