Bibliographic record
Abstract
Although there is consistent evidence that higher levels of processing, such as learning the form-meaning associations specific to the second language (L2), are a source of difficulty in acquiring L2 speech, no study has addressed how these levels interact in shaping L2 perception and production of intonation. We examine the hypothesis of whether access to contextual meaning increases the chances of first language (L1) influence on L2 intonation. To test this hypothesis, we compared the perception and production of sentential English focus by 27 advanced English language learners (n= 13 L1 Mandarin speakers;n= 14 L1 Spanish speakers) and 13 controls, through a series of tasks that promoted different levels of access to meaning. Results showed that L1 transfer was especially clear in Spanish speakers. Not only did they consistently differ from controls in their perception of focalized verbs and subjects, showing their L1 bias to perceive focus at the end of a sentence, but they were also the only group of speakers that inserted pauses after the focalized word, which showed strong L1 effects. Moreover, these L1 transfer effects were more obvious in contextualized tasks, which indicated that facilitating access to meaning by adding context increased L1 transfer effects on the perception and especially on the production of focus intonation.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".