Phonology, Semantics, and the Comprehension–Expression Gap in Emerging Lexicons
Bibliographic record
Abstract
Purpose Children come to understand many words by the end of their 1st year of life, and yet, generally by 12 months, only a few words are said. In this study, we investigated which linguistic factors contribute to this comprehension-expression gap the most. Specifically, we asked the following: Are phonological neighborhood density, semantic neighborhood density, and word frequency (WF) significant predictors of the probability that words known (understood) by children would appear in their spoken lexicons? Method Monosyllabic words in the active (understood and said) and passive (understood, not said) lexicons of 201 toddlers were extracted from the Dutch Communicative Development Inventory (Zink & Lejaegere, 2002) parent-completed forms. A generalized linear mixed-effects model was applied to the data. Results Phonological neighborhood density and WF were independently and significantly associated with whether or not a known word would be in children's spoken lexicons, but semantic neighborhood density was not. There were individual differences in the impact of WF on the probability that known words would be said. Conclusion The novel findings reported here have 2 major implications. First, they indicate that the comprehension-expression gap exists partly because the phonological distributional properties of words determine how readily words can be phonologically encoded for word production. Second, there are likely subtle and complex individual differences in how and when the statistical properties of the ambient language impact on children's emerging lexicons that might best be explored via longitudinal sampling of word knowledge and use.
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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 | 0.002 | 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 | 0.001 |
| 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".