Why are Noun-Verb-<i>er</i> compounds so difficult for English-speaking children?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Preschool children who attempt novel NV -er compounds (like cat brusher ) often misorder the noun and the verb, arguably based on sentential phrasal ordering (e.g., Clark, Hecht, & Mulford, 1986). In this study, we test this argument by replicating Clark’s prediction that children’s attempts will fall into predictable stages based on age and by comparing children’s production of NV- er compounds with another construction that violates sentential phrasal ordering: Verb- ing Noun phrases. Our studies show that we could not replicate the stages described by Clark and that children were more likely to produce Verb- ing Noun constructions in the target order than NV- er . However, the children’s constructions showed a contingency between the order of the elements and the children’s choice of morpheme, suggesting that they were often aiming for the target form. These results suggest that children do not misorder nouns and verbs in NV -er compounds because of phrasal ordering. We discuss possible alternatives for why NV -er compounds are difficult for preschool children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it