The Production of English Vowels by Fluent Early and Late Italian-English Bilinguals
Bibliographic record
Abstract
The primary aim of this study was to determine if fluent early bilinguals who are highly experienced in their second language (L2) can produce L2 vowels in a way that is indistinguishable from native speakers' vowels. The subjects were native speakers of Italian who began learning English when they immigrated to Canada as children or adults ('early' vs. 'late' bilinguals). The early bilinguals were subdivided into groups differing in amount of continued L1 use (early-low vs. early-high). In experiment 1, native English-speaking listeners rated 11 English vowels for goodness. As expected, the late bilinguals' vowels received significantly lower ratings than the early bilinguals' vowels did. Some of the early-high subjects' vowels received lower ratings than vowels spoken by a group of native English (NE) speakers, whereas none of the early-low subjects' vowels differed from the NE subjects' vowels. Most of the observed differences between the NE and early-high groups were for vowels spoken in a nonword condition. The results of experiment 2 suggested that some of these errors were due to the influence of orthography.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".