The role of type and token frequency in using past tense morphemes correctly
Why this work is in the frame
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Bibliographic record
Abstract
Type and token frequency have been thought to be important in the acquisition of past tense morphology, particularly in differentiating regular and irregular forms. In this study we tested the role of frequency in two ways: (1) in bilingual children, who typically use and hear either language less often than monolingual children and (2) cross-linguistically: French and English have different patterns of frequency of regular/irregular verbs. Ten French-English bilingual children, 10 French monolingual and 10 English monolingual children between 4 and 6 years watched a cartoon and re-told the story. The results demonstrated that the bilingual children were less accurate than the monolingual children. Their accuracy in both French and English regular and irregular verbs corresponded to frequency in the input language. These results are consistent with the hypothesis that children learn past tense morphemes by analogy with other words in their vocabularies. We propose a developmental sequence based on conservative generalization across a growing set of verbs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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