Cross-language sensitivity to phonotactic patterns in infants
Bibliographic record
Abstract
This study explored sensitivity to word-level phonotactic patterns in English and Japanese monolingual infants. Infants at the ages of 6, 12, and 18 months were tested on their ability to discriminate between test words using a habituation-switch experimental paradigm. All of the test words, neek, neeks, and neekusu, are phonotactically legitimate for English, whereas the first two words are critically noncanonical in Japanese. The language-specific phonotactical congruence influenced infants' performance in discrimination. English-learning infants could discriminate between neek and neeks at the age of 18 months, but Japanese infants could not. There was a similar developmental pattern for infants of both language groups for discrimination of neek and neeks, but Japanese infants showed a different trajectory from English infants for neekusu/neeks. These differences reflect the different status of these word patterns with respect to the phonotactics of both languages, and reveal early sensitivity to subtle phonotactic and language input patterns in each language.
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 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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".