Vowel inventory size matters: assessing cue-weighting in L2 vowel perception
Bibliographic record
Abstract
To examine whether L1 vowel inventory size could be a contributing factor to the use of temporal cues in L2 vowel perception, this study assessed the perception of English /i-ɪ/ by 66 learners of four different L1s: Danish, Portuguese, Catalan and Russian. The L2 learners performed a forced-choice identification task containing natural and duration-manipulated stimuli. Findings suggest that the participants’ over-reliance on duration cues seem to be partially related to their L1 vowel inventory size. The participants with the greatest L1 vowel inventory (Danish) demonstrated the most native-like vowel perception and the participants with the smallest L1 vowel inventory (Russian) over-relied on duration cues more than the other learners. Interestingly, the participants with somewhat comparable L1 vowel inventories (Portuguese and Catalan) performed similarly.
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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 | 0.004 |
| 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 | 0.001 |
| 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".