Accent variation and the development of speech and language abilities
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
Accent variation is a central feature of human language. As adults, we readily adapt to different varieties of our native language, but we also use accent information to make a variety of social inferences. Thus, our treatment of accents sits squarely at the intersection of language and social processing. Despite the ubiquity of accent variation and its importance in our mental lives, it was long absent from studies in the field of infant development. Although the complexities of bilingual input were recognized, the study of monolingual language development proceeded as if all infants were exposed to a single variety of their native language. This perspective shaped our theories of speech and language development. The first study to explore infants' perception of accents was published in 2000. Over the past 25 years, there has been a steady increase in work on infants' treatment of new accent varieties, their handling of multiple varieties in their natural input, and their accent-based social inferences. There is much left to be learned about just how infants navigate the rich tapestry of speech variation in their environments, but this work has already provided an important window into the nature of infants' speech representations and has upended our understanding of how early links between language and social variation are formed. We conclude our review by highlighting how understanding infants' treatment of accent variation is critical for developing models that can account for efficient speech and language development in linguistically diverse contexts.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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