On the development of null implicit objects in L1 English
Bibliographic record
Abstract
Abstract This article explores a defining property of implicit null object constructions, and how this property emerges during the L1 acquisition process. Implicit objects are non-referential and characterized by a strong semantic association between a null N in object position and the contents of the verb root. By means of an elicited production study, we examine children’s sensitivity to this association in terms of the typicality of implicit direct objects and of their use in a potentially contrastive context. Participants were 73 English-speaking children (between the ages of 2;09 and 5;08) and 20 adult controls. Our results show that children make a distinction between implicit objects with typical and atypical objects—even in scenarios where a previous use introduces a potential contrast—but at rates that differ from those of adults. This suggests an incomplete knowledge of the target properties of null objects and indicates that children use a referential null N until later in development, when the selectional link between V and the null object becomes entrenched and hyponymy with the verb root becomes the sole source of recoverability. We draw implications about the co-development of verb meaning and the null object construction.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".