Word Segmentation in Monolingual Infants Acquiring Canadian English and Canadian French: Native Language, Cross‐Dialect, and Cross‐Language Comparisons
Bibliographic record
Abstract
In five experiments, we tested segmentation of word forms from natural speech materials by 8-month-old monolingual infants who are acquiring Canadian French or Canadian English. These two languages belong to different rhythm classes; Canadian French is syllable-timed and Canada English is stress-timed. Findings of Experiments 1, 2, and 3 show that 8-month-olds acquiring either Canadian French or Canadian English can segment bi-syllable words in their native language. Thus, word segmentation is not inherently more difficult in a syllable-timed compared to a stress-timed language. Experiment 4 shows that Canadian French-learning infants can segment words in European French. Experiment 5 shows that neither Canadian French- nor Canadian English-learning infants can segment two syllable words in the other language. Thus, segmentation abilities of 8-month-olds acquiring either a stress-timed or syllable-timed language are language specific.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".