Probing rhythmic patterns in English-L2: a preliminary study on vowel reduction by Brazilian learners at different ages
Bibliographic record
Abstract
Languages are traditionally classified as mora-timed, syllable-timed or stress-timed in relation to their rhythmic patterns. The distinction between syllable-timed and stress-timed languages, however, lacks solid evidence in the literature. Syllable-timed languages typically have similar duration across unstressed and stressed syllables, whereas stress-timed languages tend to have similar inter-stress intervals, and unstressed syllables are shorter than stressed syllables. According to this categorical classification, English is a stress-timed language, thus having more reduction in unstressed vowels. Brazilian Portuguese, on the other hand, is typically classified as syllable-timed, and thus has little reduction of unstressed vowels. If these categorical rhythmic differences are correct, then acquiring the rhythmic patterns of English should be a challenging task to Brazilian learners, who are not expected to produce unstressed vowels with asmuch reduction as English native speakers. However, recent studies have found that the typology of rhythm is best understood as not categorical, but rather gradient, and that Brazilian Portuguese has a mixed classification, with more stress timing than would be expected from a traditional and categorical perspective. We therefore hypothesize that Brazilian learners of English should not have major difficulties reducing unstressed vowels, even when exposed to the second language later in life. To test this hypothesis, we analyze production data of native speakers of English (control group) and two groups of Brazilian advanced learners of English who differ in their age of initial exposure to formal instruction. The results show that neither group of learners is credibly different from the control group, which is consistent with the hypothesis that the mixed rhythm present in Brazilian Portuguese in fact facilitates the acquisition of the rhythmic patterns of English, a stress-timed language, at least in terms of unstressed vowel reduction.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".