Variable forms in French-learning toddlers’ lexical representations.
Bibliographic record
Abstract
We investigated toddlers' phonological representations of common vowel-initial words that can take on multiple surface forms in the input. In French, liaison consonants are inserted and are syllabified as onsets in subsequent vowel-initial words, for example, petit /t/ éléphant [little elephant]. We aimed to better understand the impact on children's early lexical representations of this frequent intrusion by consonants by testing whether toddlers store multiple forms for vowel-initial words (e.g., téléphant, zéléphant) early in acquisition. Thirty-one Quebec French-learning 30-month-olds completed an eye-tracking experiment (16 girls). Children were predominantly from White, middle-class families living in a large urban area (Montreal). Each trial presented two objects while one of them was named. There were four key trial types: (a) correct vowel-initial (e.g., joli éléphant [pretty elephant]); (b) pragmatically incorrect frequent intrusion (e.g., joli zéléphant, /z/ intrusion [pretty elephants], which is grammatically acceptable but does not correspond to the picture); (c) lexically incorrect frequent intrusion (e.g., joli téléphant, /t/ intrusion, as /t/ is a frequent liaison consonant in general but is impossible with joli); (d) lexically incorrect infrequent intrusion (e.g., joli géléphant, /g/ intrusion, as /g/ is an infrequent liaison consonant and is also impossible with joli). The results showed that target recognition was successful in the frequent /t/- and /z/-intrusion trials and was also evident in the vowel-initial trials, whereas it was impeded in the infrequent /g/-intrusion trials. Our findings demonstrate that French-learning children's early lexicon contains multiple variants for words that are subject to phonological alternations, including frequent liaison-consonant variants. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".