Aspiring to Aspirate: L2 Acquisition of English Word-Initial /p/ Over 10 Years
Bibliographic record
Abstract
This short report describes a longitudinal examination of the acquisition of English-aspirated stops by an initial cohort of 24 adult Slavic-language (Russian, Ukrainian, and Croatian) speakers. All had arrived in Canada with low oral English proficiency, and all were enrolled in the same language instruction program at the outset. Initial bilabial stops in CVCs were recorded at eight testing times: six during the first year of the study, again at year 7, and finally at year 10. Intelligibility was evaluated through a blind listening assessment of the stop productions from the first seven testing times. Voice onset times (VOT) were measured for /p/ from all eight times. Mean /p/ intelligibility improved-mainly during a proposed Window of Maximal Opportunity for L2 speech acquisition-but remained below 100%, even after 7 years. For some speakers, early /p/ productions were minimally aspirated, with VOT increasing over time but remaining intermediate between L1 English and L1 Slavic-Language values at 10 years. However, inter-speaker variability was dramatic, with some speakers showing full intelligibility throughout the study and others showing many unintelligible productions at all times. Individual learning trajectories tended to be non-linear and often non-cumulative. Overall, these findings point to a developmental process that varies considerably from one learner to another. It also demonstrates the serious drawbacks of relying on group means to characterize the process of L2 segmental learning.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".