Bibliographic record
Abstract
This study compares the morphosyntax of children with SLI to the morphosyntax of children acquiring a second language (L2) to determine whether the optional infinitive phenomenon (M. Rice, K. Wexler, & P. Cleave, 1995; K. Wexler, 1994) is evident in both learner groups and to what extent cross-learner similarities exist. We analyzed spontaneous production data from French-speaking children with SLI, English-speaking L2 learners of French, and French-speaking controls, all approximately 7 years old. We examined the children's use of tense morphology, temporal adverbials, agreement morphology, and distributional contingencies associated with finiteness. Our findings indicate that the use of morphosyntax by children with SLI and by L2 children has significant similarities, although certain specific differences exist. Both the children with SLI and the L2 children demonstrate optional infinitive effects in their language use. These results have theoretical and clinical relevance. First, they suggest that the characterization of the optional infinitive phenomenon in normal development as a consequence of very early neurological change may be too restrictive. Our data appear to indicate that the mechanism underlying the optional infinitive phenomenon extends to normal (second) language learning after the primary acquisition years. Second, they indicate that tense-marking difficulty may not be an adequate clinical marker of SLI when comparing children with impairment to both monolingual and bilingual peers. A more specific clinical marker would be more effective in diagnosing disordered populations in a multilingual context.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".