An examination of prosody and second language sentence processing through pause insertion
Bibliographic record
Abstract
Objectives: Research on second language (L2) sentence comprehension often has examined reliance on semantic and syntactic information but has left aside for the most part the role of prosodic cues. In the present study, we compare less- and more-proficient L2 learners’ integration of prosody and syntax structure during auditory L2 sentence comprehension. Design: Two group Chinese learners of L2 English learners (A2 and C1 levels) participated in an auditory comprehension task, which included sentences that had artificial pauses inserted either between or within syntactic boundaries. After hearing each sentence, learners were asked to judge the translation as ‘identical’ or ‘not identical’ on the keyboard. Data Analysis: We conducted t-tests and an analysis of variance to examine prosodic effects among the two learner groups. Findings: The results showed that both A2 and C1 learners were sensitive to pauses. However, the direction and magnitude of this sensitivity was significantly different for the two groups. A2 learners were faster to respond to auditory sentences in which a brief pause was placed within syntactic phrases. Contrarily, C1 learners responded faster when the brief pause was placed between syntactic phrases. Originality: Unique to the present study is the inclusion of the pause-insertion paradigm to examine the role of prosody in L2 auditory sentence processing. Implications: The results imply that the two groups of learners do not rely on prosodic and syntactic cues in the same manner when processing L2 sentences. We argue that the processing mechanisms involved in L2 sentence comprehension evolve hand-in-hand with L2 proficiency development. We discuss the implications of these findings for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".