Perceptual foundations of bilingual acquisition in infancy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Infants are prepared by biology to acquire language, but it is the native language(s) they must learn. Over the first weeks and months of life, infants learn about the sounds and sights of their native language, and use that perceptual knowledge to pull out words and bootstrap grammar. In this paper, I review research showing that infants growing up bilingual learn the properties of each of the their two languages simultaneously, while nonetheless keeping them apart. Thus, they use perceptual learning to break into the properties of each of the two native languages. While the fundamental process of language acquisition is the same whether one or two languages are being acquired, cognitive advantages accrue from the task of language separation, and processing costs accrue from the more minimal input received in each of the two languages. I conclude by suggesting that when there are sufficient cues to which language is being used, the cognitive advantages that accrue from language separation enable the bilingual infant to move forward in language acquisition even in the face of processing costs.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it