Acquisition of L2 Japanese WH questions: Evidence of phonological contiguity and non-shallow structures
Bibliographic record
Abstract
In this article we look at some of the structural properties of second language (L2) Japanese WH questions. In Japanese the WH words are licensed to remain in situ by the prosodic contiguity properties of the phrases which have no prosodic boundaries between the WH word and the question particle. In a rehearsed-reading, sentence production task, we look to see whether non-native speakers of Japanese who are learning the L2 in university classes in North America are able to acquire grammars which are constrained by such universal properties as Match Theory and Contiguity Theory. While linear mixed effects analyses of the pitch contours reveal that the L2ers have not acquired the phonetic implementation distinction of the documented pitch boost on WH words compared to non-WH DPs, our data show that the participants have acquired the pitch compression patterns indicative of having no prosodic phrases intervening between the WH word and the question particle. This property of Japanese WH questions is not taught in their classes, and, thus we argue, that the data are supportive of the position that interlanguage grammars are constrained by universal grammatical properties such as the prosodic contiguity of WH-phrase licensing. We also present these results as being counter to the Shallow Structure Hypothesis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".