Developmental language disorder in sequential bilinguals: Characterising word properties in spontaneous speech
Bibliographic record
Abstract
The current study sought to investigate whether word properties can facilitate the identification of developmental language disorder (DLD) in sequential bilinguals by analyzing properties in nouns and verbs in L2 spontaneous speech as potential DLD markers. Measures of semantic (imageability, concreteness), lexical (frequency, age of acquisition) and phonological (phonological neighbourhood, word length) properties were computed for nouns and verbs produced by 15 sequential bilinguals (5;7) with DLD and 15 age-matched controls with diverse L1 backgrounds. Linear mixed modelling revealed a significant interaction of group and word category on phonological neighbourhood values but no differences across imageability, concreteness, frequency, age of acquisition, and word length measures in spontaneous speech. Outcomes suggest that group-level differences may not be apparent at the word-level, due to the heterogeneous nature of DLD and potential similarities in production during early L2 acquisition.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".