Learning to liaise and elide<i>comme il faut</i>: evidence from bilingual children*
Bibliographic record
Abstract
Liaison and elision in French are phonological phenomena that apply across word boundaries. French-speaking children make errors in contexts where liaison/elision typically occurs in adult speech. In this study, we asked if acquisition of French liaison/elision can be explained in a constructivist framework. We tested if children's liaison/elision was sensitive to co-occurrence and meaning. We expected children's use of liaison/elision to correlate with their experience with French (estimated by vocabulary). Thirty-one French-speaking children (twenty-five bilingual) between three and five years old produced familiar vowel-initial words, following four words: (1) un, (2) deux, (3) un petit and (4) beaucoup de. The children with smaller French vocabularies produced many vowel-initial words and some consonant-initial chunks. The children with larger French vocabularies produced liaison/elision correctly across several frames while associating a number interpretation with liaised consonants. These results suggest that children use a variety of cues to construct the appropriate use of liaison/elision.
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.
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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".