Animacy in the acquisition of differential object marking by Romanian monolingual children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Differential object marking (DOM) has been shown, in an impressive number of production studies, to be acquired by monolingual children at around age 3. The picture which emerges from comprehension data, however, reveals that DOM is an area of vulnerability in L1 acquisition. This study investigates the acquisition of DOM by monolingual Romanian children using a preference judgment task. 80 monolingual Romanian children (aged 4;04-11;04) and a control group of 10 Romanian adults took part in the study. Results show that DOM is vulnerable and trace this vulnerability to the animacy feature. Romanian children incorrectly overgeneralize DOM to inanimate proper names and inanimate descriptive DPs until age 9. The vulnerability of animacy is predicted by its variable behaviour with respect to object marking as well as by the current increase in the use of clitic doubling, a DOM marker less sensitive to animacy. On the learnability side, we account for the findings in terms of Biberauer & Roberts’ (2015, 2017) Maximize Minimal Means model. We suggest that, in accordance with the Feature Economy bias, Romanian children first identify only the role of referential stability (which has more robust cues in the input) and consider the possibility of animacy as a relevant feature later. In line with the Input Generalization bias, children maximize the role of referential stability which results in overgeneralization of DOM to inanimate objects, especially to inanimate proper names.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it