Mandarin-speaking two-year-olds’ comprehension of complement control
Bibliographic record
Abstract
Abstract The present study investigates early acquisition of complement control by Mandarin-speaking children. We tested thirty-two Mandarin-speaking 2-month-olds in a comprehension experiment adopting the Intermodal Preferential Looking Paradigm and assessed their ability to choose the right controller of the empty subject PRO. Speech stimuli included four sentence types: subject control xiang ‘want’ sentences, covert object control rang ‘let’ sentences, overt object control jiao ‘ask’ sentences and benefactive coverb gei ‘for’ sentences. It was found that when comprehending test sentences with two potential antecedents, children’s target looking was significantly above chance by looking more to the subject picture in subject control xiang trials and non-control gei trials, and that a marginal significant difference was identified for the two minimal pairs (subject control xiang vs. covert object control rang , non-control gei vs. overt object jiao ). The results also point to a stronger sensitivity to subject control than to object control. These results show that Mandarin-speaking children who have just entered their second year in life are already sensitive to control, suggesting their emerging knowledge of some basic syntactic properties of complement control.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".