Mandarin-learning 19-month-old toddlers’ sensitivity to word order cues that differentiate unaccusative and unergative verbs
Bibliographic record
Abstract
Abstract Languages employ different means to manifest the unaccusative-unergative distinction. In Mandarin Chinese, unaccusative verbs are allowed in the inversion construction “V- le NP”, while unergative verbs are not. This grammaticality contrast brings a presence/absence contrast between the two verb classes in the inversion construction in the input. Using an eye fixation task, we investigated whether Mandarin-learning 19-month-olds were sensitive to this specific input frequency contrast. We found that infants distinguished the grammatical versus ungrammatical uses of the two verb classes in the inversion construction “V- le NP” (Experiment 1). When the verb classes were in the “NP V- le ” order (Experiment 2) (i.e., the same level of grammaticality), infants showed no evidence of a looking difference. These responses indicate toddlers’ sensitivity to the distribution of the two verb classes in the inversion construction. This distributional information is likely to be one of the potential cues that facilitate their acquisition of the unaccusative-unergative distinction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".