Can prosody encode recursive embedding? Children's realizations of complex NPs in Japanese
Bibliographic record
Abstract
Recursive NPs are difficult to produce and late to emerge. We compare prosodic and syntactic abilities in Japanese-speaking five- and six-year-olds (n = 28) and adults (n = 10). It is reported that syntactic structure in Japanese is prosodically marked via downstep and metrical boost. Results of an elicited imitation task suggested that children had acquired the lexical prosody (contrast between accented and unaccented words), a pre-requisite for downstep realization. While downstep, the prosodic phrasing involved in the complex NPs in this study, was established, children showed interspeaker variation with the metrical boost, a feature that distinguishes recursively embedded NPs from non-recursive NPs. However, variability was also found in adults, indicating that, in contrast to previous results, prosodic encoding of syntax is generally unreliable in adult speech. Finally, the magnitude of metrical boost was not correlated to children's ability to produce recursive possessives, suggesting that prosody does not help bootstrap Japanese children's recursive phrases.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".