VOT drift in 3 generations of heritage language speakers in Toronto
Why this work is in the frame
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Bibliographic record
Abstract
Results for onset /p, t, k/ produced by 34 individuals representing three generations of Russian, Ukrainian, and Italian, are presented. Data when compared to published reports on monolingual patterns shows that ML speakers' Voice onset time (VOT) tends to drift from the homeland standard toward that of English in successive generations. VOT was examined in conversational speech of 3-4 speakers in each generation in each language, plus one fluent G5 Ukrainian. Results show that mean VOT for Russian and Ukrainian increases as generations progress, as predicted. However, Italian exhibits stability across generations. Positive deviation from the mean indicates longer, more English-like VOT. Russian and Ukrainian show the predicted shorter VOT correlating with higher Ethnic Orientation Questionnaire (EOQ), while Italian has the opposite trend.
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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) | 0.004 | 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 it