Children do not ignore (null objects): Against deficit accounts of the null object stage in language acquisition
Bibliographic record
Abstract
Children across a variety of languages omit direct objects at higher rates that adults. It has been argued that these omissions arise from children’s performance or pragmatic limitations. The null object approach holds that children start by allowing a broader set of mechanisms for the recoverability of null objects than those possible in the adult grammar, which becomes more restricted with experience. Comprehension data is considered key evidence for evaluating representational approaches, but the interpretation of previous comprehension results is obscured by methodological issues. This article presents new data contrasting the interpretation of various types of direct objects in negative sentences, including null objects (Johnny is not eating) and anaphoric and negative polarity items (not eating it/not eating anything). English-speaking children aged 4–5 (n = 75) participated in three separate comprehension studies contrasting the interpretation of null objects to overt objects. Children consistently accepted sentences with overt anaphoric objects and rejected sentences with negative polarity objects, and treated sentences with null objects as fully ambiguous.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".