A Study of rhythm in London: is syllable-timing a feature of multicultural London English?
Bibliographic record
Abstract
Recent work on London English has found innovation in inner city areas, most likely as the outcome of dialect contact. These innovations are shared by speakers of different ethnic backgrounds, and have been identified as features of Multicultural London English (MLE). This study examines whether syllable timing is a feature of MLE, as work on rhythm shows that dialect and language contact may lead to varieties of English becoming more syllable-timed. We hypothesized that MLE speakers would also show suprasegmental innovations, having more syllable-timed rhythm than what has been reported for British English. Narratives as told by teenagers of different ethnic backgrounds, elderly speakers born between 1920 and 1935 and speakers born between 1874 and 1895 were extracted from interviews. The speech was segmented into consonantal and vocalic elements by forced phonemic alignment. Measurements of vocalic nPVI, as an indicator of rhythmic patterns, were calculated. Overall, the inner-London speakers were more syllable-timed than what has been found for British English. The results revealed that young speakers of non-Anglo background were significantly more syllable-timed than young Anglo speakers. The relatively low nPVI for all inner-London speaker groups may indicate the capital’s status as a centre of linguistic innovation and long-standing migration. The results of the present study combined with work on other varieties reinforces the idea that the tendency for English to become more syllable-timed is a global phenomenon fuelled by language and dialect contact.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".