Down two steps: Are bilinguals delayed in the acquisition of recursively embedded PPs?
Bibliographic record
Abstract
The present study examines whether bilingual children are delayed in the ability to produce complex DPs. We elicited production of DPs containing two PP modifiers, in two conditions designed to tease apart the acquisition of an embedding rule from the acquisition of the recursivity of an embedding rule. In the recursive condition, one modifier PP was itself modified by an additional PP. In the non-recursive condition, both PPs sequentially modified the main noun. Participants were 71 English monolingual children and 35 bilinguals between the ages of four and six. The evidence suggested an overall difference between groups, however further analysis revealed that bilinguals differed from monolinguals only insofar as the onset of PP embedding. No specific additional bilingual delay arose from the recursive condition. This suggests that recursive embedding is a resilient domain in language acquisition and supports proposals that link morphosyntactic delays in bilingual children to domains of grammar that are heavily reliant on lexical learning, which would include learning the first instance of PP embedding. --------------------------------------------------------------------------------- DOIS PASSOS ABAIXO: ESTÃO OS BILÍNGUES ATRASADOS NA AQUISIÇÃO DE PPs ENCAIXADOS RECURSIVAMENTE? Este artigo investiga se as crianças bilíngues estariam atrasadas em relação à produção de DPs complexos. Eliciamos a produção de DPs contendo dois PPs modificadores, em duas condições, planejadas para distinguir a aquisição da regra de encaixamento da aquisição da recursividade de uma regra de encaixamento. Na condição recursiva, um PP modificador era, por sua vez, modificado por um PP adicional. Na condição não-recursiva, ambos PPs modificavam sequencialmente o nome. Participaram 71 crianças monolíngues de inglês e 35 bilíngues entre as idades de quatro e seis anos. Os resultados sugerem uma diferença entre os grupos. No entanto, análises mais detalhadas revelam que os bilíngues diferem dos monolíngues apenas no que diz respeito ao início de produção de PPs encaixados. Não se constatam atrasos adicionais relativos à condição recursiva. Isso sugere que o encaixamento recursivo é um domínio resiliente na aquisição de linguagem e oferece suporte a propostas que vinculam atrasos morfossintáticos em crianças bilíngues a domínios da gramática que dependem fortemente da aprendizagem lexical, o que incluiria a aprendizagem da primeira instância de um PP encaixado. --- Artigo em inglês. --- DOI: http://dx.doi.org/10.12957/matraga.2017.28781
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".