Disentangling bilingualism and developmental language disorder in the acquisition of Spanish articles and clitics: Quantitative and qualitative contributions
Bibliographic record
Abstract
This study explored the acquisition of Spanish nominal morphology in 116 children aged 4;0 to 6;11, grouped according to language ability (developmental language disorder [DLD] and typical development [TD]) and bilingualism (Spanish-English bilingual and Spanish monolingual). Monolinguals produced more target-like articles and direct object clitics than bilinguals, as did children with TD compared to peers with DLD. Bilinguals with TD produced more target-like morphology than monolinguals with DLD, particularly clitics. Children with DLD were more likely to omit clitics than peers with TD, but this contrast did not extend to bilinguals compared to monolinguals. Children produced singular default articles in plural contexts. Overall, our results suggest that clitics function better than articles for identifying DLD in bilinguals on quantitative and qualitative grounds.
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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 | 0.000 |
| 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 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".