Growing up bilingual: examining the language input and word segmentation abilities of bilingual infants
Bibliographic record
Abstract
Infants’ early language experiences play a critical role on their language development. In this dissertation, I explored the nature of this relationship in a bilingual context. Specifically, I investigated how bilingual caregivers are providing language input to their infants, and how global measures of this bilingual experience affect early word segmentation (i.e., the ability to recognize words in a sentential context). This work is important for understanding the factors that contribute to the developmental trajectory and processing capacities of bilingual infants. In the first part of this dissertation, I assessed research methods for examining the language input to bilingual infants. To do so, I recruited twenty-one French-English bilingual families with a 10-month-old infant from Montréal, Canada. These families completed language interviews and contributed three full-day recordings at home using the LENA (Language Environment Analysis) recording system. Chapter 2 provides support for using the LENA recording system for investigating the language input in bilingual infants, and Chapter 3 shows that caregivers are reliable at describing their infants’ language experience at home. Next, I described the variability in language experiences within bilingual infants, and how these language experiences might affect word segmentation. In Chapter 4, I recruited 8- and 10-month-old infants from monolingual and bilingual homes. Our findings confirm that monolingual infants can segment bisyllabic words in their native language, but not a non-native language. Critically, our findings reveal that some bilingual infants are able to segment bisyllabic words in both of their native languages by 8-months of age. Interestingly, exploratory analyses suggest that infants’ word segmentation skills in our dual-language task are bolstered if they hear more language mixing from their caregivers. In sum, this dissertation contributes to the growing literature that highlights the wide variability in bilingual language experiences, and their effects on early speech processing skills. Indeed, examining the language experiences and skills of bilingual-learning infants provides us with a unique lens for investigating language acquisition and development.
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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 | 0.000 |
| 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 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".